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Director, Data Architecture

Pay
USD 195,000–225,000/yearAnnual period assumed. Location-specific pay — pay source
- Compensation and Benefits Salary Range $195,000.00 - $225,000.00 USD Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.
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Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Lead, mentor and grow the architects and engineers across five data domains

  • Design conceptual, logical and physical data models on Snowflake

  • Define and manage enterprise data products with documentation and reliability

  • Approve architecturally significant pull requests as final design authority

  • Monitor and reduce Snowflake costs and optimize high-cost pipelines

From the employer’s posting
Lead, mentor, and grow the Architects and Engineers who own our Finance, Supply Chain, Global Technology (R&D), Sustainability, and Master Data domains
Create comprehensive conceptual, logical, and physical data models across the domains you lead, utilizing Snowflake best practices
Define and manage "Data Products" across the domains you lead.
Serve as final approver on architecturally significant PRs
monitor Snowflake resource consumption (FinOps)

What you’ll bring

All qualifications

Core experience

  • Experience: 10+ years of experience in data architecture, data modeling, and data management, including a demonstrable track record of leading senior architects and engineers across multiple concurrent domains or workstreams.
  • Knowledge of data warehousing/data lakes (e.g., Snowflake, Databricks, GCP BigQuery, and open table formats like Iceberg or Delta Lake).
  • Experience with transformation tools like dbt or Coalesce.
  • Hands-on experience architecting on at least one major cloud platform
  • Deep understanding of modeling methodologies (relational, dimensional, NoSQL).
  • Strong SQL skills and experience modeling on both transactional source systems (e.g., PostgreSQL, MySQL, SQL Server) and analytical cloud data warehouses (Snowflake, BigQuery, Databricks).

Preferred experience

  • GCP preferred; AWS or Azure acceptable
Qualification wording
Experience: 10+ years of experience in data architecture, data modeling, and data management, including a demonstrable track record of leading senior architects and engineers across multiple concurrent domains or workstreams.
Knowledge of data warehousing/data lakes (e.g., Snowflake, Databricks, GCP BigQuery, and open table formats like Iceberg or Delta Lake).
Experience with transformation tools like dbt or Coalesce.
Hands-on experience architecting on at least one major cloud platform (GCP preferred; AWS or Azure acceptable).
Deep understanding of modeling methodologies (relational, dimensional, NoSQL).
Strong SQL skills and experience modeling on both transactional source systems (e.g., PostgreSQL, MySQL, SQL Server) and analytical cloud data warehouses (Snowflake, BigQuery, Databricks).
Education & alternatives
Qualifications - Education: Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field. - Experience: 10+ years of experience in data architecture, data modeling, and data management, including a demonstrable track record of leading senior architects and engineers across multiple concurrent domains or workstreams.

About Colgate-Palmolive

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition.

In the employer’s words · Read in context

Apply at Colgate-Palmolive

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 2026today
Recorded sightings
2
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$154K–$225K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,958 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 7 and day 53.

From 7,797 similar postings that came down. Coming down is not always a hire.

Colgate-Palmolive is hiring

38 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Leadership hiring is steady
  • Takes jobs down at a usual pace
  • 3% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • AWS
  • Azure
  • BigQuery
  • Databricks
  • dbt
  • Delta Lake
  • Fivetran
  • GCP
  • Iceberg
  • Kubernetes
  • MySQL
  • NoSQL
  • PostgreSQL
  • Sigma
  • Snowflake
  • SQL Server
  • Terraform
  • Airflow
Where the posting names them
- Data Modeling: Expert-level proficiency in dimensional data modeling (Star Schema, Snowflake Schema, fact/dimension design) and the dbt-style layered architecture (raw → staging → intermediate → marts). Ability to map complex business processes to data structures. Experience with data modeling & diagramming tools. - Modern Data Stack: Deep hands-on experience with Snowflake or any cloud data warehouse (architecture, performance tuning, security, multi-account / federated patterns, data sharing) and dbt or similar SQL-based data transformation tools (project structure, macros, testing, documentation). - Orchestration & Infrastructure: Solid understanding of Airflow (on Kubernetes / GKE) DAG design patterns and dependencies. Hands-on experience with Infrastructure-as-Code (Terraform) for provisioning Snowflake and cloud resources, GitHub-based CI/CD (e.g., GitHub Actions), and secret management (e.g., HashiCorp Vault).
- Strong grasp of integration patterns (ETL, ELT, API integrations). - Strong SQL skills and experience modeling on both transactional source systems (e.g., PostgreSQL, MySQL, SQL Server) and analytical cloud data warehouses (Snowflake, BigQuery, Databricks). - Governance: Familiarity with data governance principles, data quality management tools, and practices.
- Experience with transformation tools like dbt or Coalesce. - Hands-on experience architecting on at least one major cloud platform (GCP preferred; AWS or Azure acceptable). - Deep understanding of modeling methodologies (relational, dimensional, NoSQL).
- Technical Knowledge: - Knowledge of data warehousing/data lakes (e.g., Snowflake, Databricks, GCP BigQuery, and open table formats like Iceberg or Delta Lake). - Experience with transformation tools like dbt or Coalesce.
- Design & Architect: Create comprehensive conceptual, logical, and physical data models across the domains you lead, utilizing Snowflake best practices (clustering, micro-partitions) to ensure performance. - Apply & Extend Standards: Adopt and operationalize the enterprise dbt project structure, modeling conventions and testing frameworks across all owned domains. Identify and propose domain-specific extensions back through the central team's review process where domain needs warrant. - Collaborate: Partner with the Data Delivery Leads to ensure architectural integrity during sprint execution, and work with the Central Data Platform Team to request and configure necessary infrastructure resources.
- Collaborate: Partner with the Data Delivery Leads to ensure architectural integrity during sprint execution, and work with the Central Data Platform Team to request and configure necessary infrastructure resources. - Approve: Serve as final approver on architecturally significant PRs — new sources, new dbt project structures, model contracts, cross-domain dependencies. Day-to-day pipeline PRs are owned by the Data Delivery Lead. - Govern: Implement granular security policies (Row-Level Security, Dynamic Masking) and ensure all data assets are cataloged with clear lineage and metadata.
Technical Expertise: - Data Modeling: Expert-level proficiency in dimensional data modeling (Star Schema, Snowflake Schema, fact/dimension design) and the dbt-style layered architecture (raw → staging → intermediate → marts). Ability to map complex business processes to data structures. Experience with data modeling & diagramming tools. - Modern Data Stack: Deep hands-on experience with Snowflake or any cloud data warehouse (architecture, performance tuning, security, multi-account / federated patterns, data sharing) and dbt or similar SQL-based data transformation tools (project structure, macros, testing, documentation).
- Knowledge of data warehousing/data lakes (e.g., Snowflake, Databricks, GCP BigQuery, and open table formats like Iceberg or Delta Lake). - Experience with transformation tools like dbt or Coalesce. - Hands-on experience architecting on at least one major cloud platform (GCP preferred; AWS or Azure acceptable).
- Industry Experience: Experience in Retail or CPG domains. - Certifications: Relevant certifications such as Certified Data Management Professional (CDMP) or cloud-specific data certifications (eg., Snowpro Advanced Architect, dbt Analytics Engineer, or GCP Professional Cloud Architect / Professional Data Engineer) - Skills: Excellent communication, presentation, interpersonal, and problem-solving skills.
- Analytics Integration: Understanding of how BI tools (Domo, Sigma, Retool, or similar) ingest and query data, with the ability to design models that ensure fast, interactive dashboard performance. - Ingestion: Familiarity with managed replication tools (HVR, Fivetran, Qlik Replicate) for landing ERP and operational data into a cloud warehouse, and the architectural implications of CDC vs. snapshot patterns. Professional Skills:
- Optimize: Perform regular reviews of high-cost queries and data pipelines; re-architect inefficient flows to reduce Snowflake credit consumption and improve report performance. - Evaluate: Assess new features (e.g., Iceberg tables) and tools to determine their fit for the domains’ evolving needs. What You Bring to the Table
- Modern Data Stack: Deep hands-on experience with Snowflake or any cloud data warehouse (architecture, performance tuning, security, multi-account / federated patterns, data sharing) and dbt or similar SQL-based data transformation tools (project structure, macros, testing, documentation). - Orchestration & Infrastructure: Solid understanding of Airflow (on Kubernetes / GKE) DAG design patterns and dependencies. Hands-on experience with Infrastructure-as-Code (Terraform) for provisioning Snowflake and cloud resources, GitHub-based CI/CD (e.g., GitHub Actions), and secret management (e.g., HashiCorp Vault). - Analytics Integration: Understanding of how BI tools (Domo, Sigma, Retool, or similar) ingest and query data, with the ability to design models that ensure fast, interactive dashboard performance.
- Hands-on experience architecting on at least one major cloud platform (GCP preferred; AWS or Azure acceptable). - Deep understanding of modeling methodologies (relational, dimensional, NoSQL). - Strong grasp of integration patterns (ETL, ELT, API integrations).
- Orchestration & Infrastructure: Solid understanding of Airflow (on Kubernetes / GKE) DAG design patterns and dependencies. Hands-on experience with Infrastructure-as-Code (Terraform) for provisioning Snowflake and cloud resources, GitHub-based CI/CD (e.g., GitHub Actions), and secret management (e.g., HashiCorp Vault). - Analytics Integration: Understanding of how BI tools (Domo, Sigma, Retool, or similar) ingest and query data, with the ability to design models that ensure fast, interactive dashboard performance. - Ingestion: Familiarity with managed replication tools (HVR, Fivetran, Qlik Replicate) for landing ERP and operational data into a cloud warehouse, and the architectural implications of CDC vs. snapshot patterns.
- Governance Implementation: Operationalize the enterprise-wide standards and the broader governance framework across the domains you lead. This includes implementing data quality checks, enforcing privacy controls (data masking), managing metadata/lineage, and ensuring strict adherence to security policies. - Solution Optimization & Cost Management: Act as the "Design Authority" across the domains you lead. You will proactively optimize pipeline performance, monitor Snowflake resource consumption (FinOps), and ensure all solutions are architected for long-term scalability and cost-efficiency. Day-to-Day Activities
Day-to-Day Activities - Design & Architect: Create comprehensive conceptual, logical, and physical data models across the domains you lead, utilizing Snowflake best practices (clustering, micro-partitions) to ensure performance. - Apply & Extend Standards: Adopt and operationalize the enterprise dbt project structure, modeling conventions and testing frameworks across all owned domains. Identify and propose domain-specific extensions back through the central team's review process where domain needs warrant.
- Govern: Implement granular security policies (Row-Level Security, Dynamic Masking) and ensure all data assets are cataloged with clear lineage and metadata. - Optimize: Perform regular reviews of high-cost queries and data pipelines; re-architect inefficient flows to reduce Snowflake credit consumption and improve report performance. - Evaluate: Assess new features (e.g., Iceberg tables) and tools to determine their fit for the domains’ evolving needs.

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

No Relocation Assistance Offered
Job Number #176923 - Piscataway, New Jersey, United States

Who We Are

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!

Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.

 

We are seeking a highly experienced Data Architect Lead to spearhead the definition, design, and governance of data assets across the Enterprise Data Applications organization within Global IT. In this senior leadership role, you will lead and mentor the Architects and Engineers responsible for our Finance, Supply Chain, Global Technology (R&D), Sustainability, and Master Data domains — setting architectural direction, raising the bar for engineering quality, and ensuring our data remains consistent, high-quality, secure, and accessible to support strategic business initiatives across the enterprise. You will partner closely with senior business stakeholders, delivery leads, data engineers, data scientists, and enterprise architects to build robust data models and integration strategies, and you will develop the talent and standards that scale our data organization.

What You Own (Strategic Accountability)

  1. Team & Architecture Leadership: Lead, mentor, and grow the Architects and Engineers who own our Finance, Supply Chain, Global Technology (R&D), Sustainability, and Master Data domains. Set architectural direction, uphold engineering standards, and cultivate a strong, cohesive data organization.

  2. Enterprise Data Strategy: Translate business goals across Finance, Supply Chain, Global Technology (R&D), Sustainability, and Master Data into a robust, forward-looking data architecture roadmap. You will ensure that our technical design directly solves critical business problems rather than just moving data.

  3. Business Logic Modeling: Own the design and lifecycle of logical and physical data models across the domains you lead. You will ensure complex business rules are accurately codified, versioned, and optimized for analytics consumption in BI reporting tools.

  4. Data Product Ownership: Define and manage "Data Products" across the domains you lead. You will ensure that datasets exposed to the wider enterprise are well-documented, reliable, standardized, and interoperable across Finance, Supply Chain, R&D, Sustainability, and Master Data.

  5. Governance Implementation: Operationalize the enterprise-wide standards and the broader governance framework across the domains you lead. This includes implementing data quality checks, enforcing privacy controls (data masking), managing metadata/lineage, and ensuring strict adherence to security policies.

  6. Solution Optimization & Cost Management: Act as the "Design Authority" across the domains you lead. You will proactively optimize pipeline performance, monitor Snowflake resource consumption (FinOps), and ensure all solutions are architected for long-term scalability and cost-efficiency.

Day-to-Day Activities

  • Design & Architect: Create comprehensive conceptual, logical, and physical data models across the domains you lead, utilizing Snowflake best practices (clustering, micro-partitions) to ensure performance.

  • Apply & Extend Standards: Adopt and operationalize the enterprise dbt project structure, modeling conventions and testing frameworks across all owned domains. Identify and propose domain-specific extensions back through the central team's review process where domain needs warrant.

  • Collaborate: Partner with the Data Delivery Leads to ensure architectural integrity during sprint execution, and work with the Central Data Platform Team to request and configure necessary infrastructure resources.

  • Approve: Serve as final approver on architecturally significant PRs — new sources, new dbt project structures, model contracts, cross-domain dependencies. Day-to-day pipeline PRs are owned by the Data Delivery Lead.

  • Govern: Implement granular security policies (Row-Level Security, Dynamic Masking) and ensure all data assets are cataloged with clear lineage and metadata.

  • Optimize: Perform regular reviews of high-cost queries and data pipelines; re-architect inefficient flows to reduce Snowflake credit consumption and improve report performance.

  • Evaluate: Assess new features (e.g., Iceberg tables) and tools to determine their fit for the domains’ evolving needs.

What You Bring to the Table

Technical Expertise:

  • Data Modeling: Expert-level proficiency in dimensional data modeling (Star Schema, Snowflake Schema, fact/dimension design) and the dbt-style layered architecture (raw → staging → intermediate → marts). Ability to map complex business processes to data structures. Experience with data modeling & diagramming tools.

  • Modern Data Stack: Deep hands-on experience with Snowflake or any cloud data warehouse (architecture, performance tuning, security, multi-account / federated patterns, data sharing) and dbt or similar SQL-based data transformation tools (project structure, macros, testing, documentation).

  • Orchestration & Infrastructure: Solid understanding of Airflow (on Kubernetes / GKE) DAG design patterns and dependencies. Hands-on experience with Infrastructure-as-Code (Terraform) for provisioning Snowflake and cloud resources, GitHub-based CI/CD (e.g., GitHub Actions), and secret management (e.g., HashiCorp Vault).

  • Analytics Integration: Understanding of how BI tools (Domo, Sigma, Retool, or similar) ingest and query data, with the ability to design models that ensure fast, interactive dashboard performance.

  • Ingestion: Familiarity with managed replication tools (HVR, Fivetran, Qlik Replicate) for landing ERP and operational data into a cloud warehouse, and the architectural implications of CDC vs. snapshot patterns.

Professional Skills:

  • Strategic Thinking: Ability to see the "big picture" and design systems that persist beyond the current sprint.

  • Communication: Excellent ability to translate technical concepts into business language for stakeholders and vice-versa.

  • Leadership: Proven experience leading and mentoring senior architects and engineers across multiple concurrent domains, with a track record of setting technical direction, coaching individual contributors, and raising engineering standards.

Qualifications

  • Education: Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field.

  • Experience: 10+ years of experience in data architecture, data modeling, and data management, including a demonstrable track record of leading senior architects and engineers across multiple concurrent domains or workstreams.

  • Technical Knowledge:

    • Knowledge of data warehousing/data lakes (e.g., Snowflake, Databricks, GCP BigQuery, and open table formats like Iceberg or Delta Lake).

    • Experience with transformation tools like dbt or Coalesce.

    • Hands-on experience architecting on at least one major cloud platform (GCP preferred; AWS or Azure acceptable).

    • Deep understanding of modeling methodologies (relational, dimensional, NoSQL).

    • Strong grasp of integration patterns (ETL, ELT, API integrations).

    • Strong SQL skills and experience modeling on both transactional source systems (e.g., PostgreSQL, MySQL, SQL Server) and analytical cloud data warehouses (Snowflake, BigQuery, Databricks).

  • Governance: Familiarity with data governance principles, data quality management tools, and practices.

Preferred Qualifications

  • Cross-Domain Leadership: Experience designing data solutions across multiple enterprise business domains (e.g., Finance, Supply Chain, R&D, Sustainability, or Master Data) and leading distributed data teams is a plus

  • Industry Experience: Experience in Retail or CPG domains.

  • Certifications: Relevant certifications such as Certified Data Management Professional (CDMP) or cloud-specific data certifications (eg., Snowpro Advanced Architect, dbt Analytics Engineer, or GCP Professional Cloud Architect / Professional Data Engineer)

  • Skills: Excellent communication, presentation, interpersonal, and problem-solving skills.

  •  


Compensation and Benefits
Salary Range $195,000.00 - $225,000.00 USD

Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.

Benefits: Salaried employees enjoy a comprehensive benefits package, including medical, dental, vision, basic life insurance, paid parental leave, disability coverage, and participation in the 401(k) retirement plan with company matching contributions subject to eligibility requirements. Additional benefits include a minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours) and 13 paid holidays (vacation days are prorated based on the employee's hire date within the calendar year). Paid sick leave is adjusted based on role and location in accordance with local laws. Detailed information regarding paid sick leave entitlements will be provided to employees upon hiring and may be subject to adjustments based on changes in legislation or company policies.

Our Commitment to Inclusion
Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives  to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business.

Equal Opportunity Employer
Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law.

Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation.

For additional Colgate terms and conditions, please click here.

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Pay
- Compensation and Benefits Salary Range $195,000.00 - $225,000.00 USD Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.
Location & working pattern

Piscataway, NJ, US

For additional Colgate terms and conditions, please click here. #LI-Hybrid
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