Pay
$154K–$226K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,007 postings in the last year. Stated ranges, not salaries paid.
Principal Data Engineer
Reads like a Data Leadership role: running a data team.
Houston or Dallas, TX
Live, first seen by us 66 days ago- Pay
- Pay not listedSimilar roles state $154K–$226K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingLead architecture and delivery of enterprise data platform and analytics solutions for clients
Advise client technology and data leaders on data strategy and roadmaps
Design data pipelines and remain hands-on in code reviews and proofs of concept
Build ETL/ELT pipelines, data models, and data products
Mentor senior, mid-level, and junior data engineers
From the employer’s posting
Lead the end-to-end architecture, design, and delivery of enterprise data engineering, data platform, and analytics solutions for client engagements.
Serve as a trusted technical advisor to client stakeholders, including technology leaders, data leaders, architects, and business partners.
Remain hands-on in engineering work, including designing data pipelines, reviewing code, building proof of concepts, resolving complex technical issues, and establishing engineering patterns.
Lead the development of robust ETL/ELT pipelines, data models, data APIs, semantic layers, and data products.
Mentor senior, mid-level, and junior data engineers; provide technical coaching, career guidance, design feedback, and hands-on support.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 3, 202666 days ago
- Recorded sightings
- 40
- Last seen by us
- Nov 8, 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
Time since we first saw it
Day 66
Up longer than most. Similar jobs usually come down between day 7 and day 55.
From 8,398 similar postings that came down. Coming down is not always a hire.
CG Infinity is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
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.
- C#
- Java
- Python
- Scala
- SQL
- AWS
- Azure
- BigQuery
- Databricks
- dbt
- Docker
- Hadoop
- Kafka
- Kubernetes
- Looker
- Power BI
- Prefect
- Redshift
- SAP
- Snowflake
- Spark
- Tableau
- Terraform
- Airflow
- Dagster
- GCP
Where the posting names them
- Demonstrated experience architecting and delivering enterprise-scale data platforms and data integration solutions. - Strong hands-on expertise in SQL and at least one modern programming language, preferably Python, Scala, Java, or C#. - Strong experience with ETL/ELT design, data pipeline development, data transformation frameworks, orchestration, and workflow automation.
- Architect and implement batch, real-time, streaming, and event-driven data solutions as appropriate for client needs. - Design modern cloud data platforms using technologies such as Snowflake, Databricks, Microsoft Fabric, Azure Data Factory, AWS Glue, Amazon Redshift, BigQuery, or equivalent platforms. - Lead the development of robust ETL/ELT pipelines, data models, data APIs, semantic layers, and data products.
- Strong experience with ETL/ELT design, data pipeline development, data transformation frameworks, orchestration, and workflow automation. - Experience with one or more cloud providers: Microsoft Azure, AWS, or Google Cloud Platform. - Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies.
- Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies. - Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools. - Knowledge of distributed data-processing technologies such as Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable platforms.
Preferred Qualifications- Experience designing data platforms that support AI, machine learning, generative AI, retrieval-augmented generation, feature stores, vector databases, or advanced analytics workloads. - Certifications in AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, or other relevant data technologies. - Experience with master data management, data cataloging, data governance, privacy, regulatory compliance, or data stewardship programs.
- Experience with one or more cloud providers: Microsoft Azure, AWS, or Google Cloud Platform. - Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies. - Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools.
- Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms. - Experience with containerization and cloud-native technologies such as Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi. - Prior experience contributing to proposals, estimates, statements of work, or technical sales pursuits.
- Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools. - Knowledge of distributed data-processing technologies such as Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable platforms. - Experience designing both batch and near-real-time or streaming data solutions.
- Experience with Salesforce, SAP, ERP, CRM, finance, supply-chain, healthcare, retail, manufacturing, or other enterprise operational data domains. - Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms. - Experience with containerization and cloud-native technologies such as Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi.
- Experience with tools such as Collibra, Alation, Microsoft Purview, Unity Catalog, Informatica, Monte Carlo, Great Expectations, or similar governance and observability platforms. - Experience with Salesforce, SAP, ERP, CRM, finance, supply-chain, healthcare, retail, manufacturing, or other enterprise operational data domains. - Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms.
Your next step
Complete your application on cginfinity.applytojob.com. The employer’s form will show what is required.
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Already applied? Track this application
Demand for Data Leadership roles
New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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
We are seeking a Principal Data Engineer to lead the architecture, design, and delivery of modern data platforms and analytics solutions for clients. This is a hands-on technical leadership role for someone who can move comfortably between executive-level client conversations, solution architecture, engineering delivery, and mentoring high-performing data teams.
The ideal candidate combines deep data-engineering expertise with strong consulting instincts: they can translate business objectives into scalable technical solutions, communicate complex concepts through clear presentations, and guide teams from discovery through implementation and operationalization.
Key Responsibilities
The ideal candidate combines deep data-engineering expertise with strong consulting instincts: they can translate business objectives into scalable technical solutions, communicate complex concepts through clear presentations, and guide teams from discovery through implementation and operationalization.
Key Responsibilities
- Lead the end-to-end architecture, design, and delivery of enterprise data engineering, data platform, and analytics solutions for client engagements.
- Serve as a trusted technical advisor to client stakeholders, including technology leaders, data leaders, architects, and business partners.
- Facilitate discovery sessions, requirements workshops, technical assessments, architecture reviews, and solution-design discussions.
- Translate business goals, data challenges, and operating-model requirements into practical data strategies, roadmaps, reference architectures, and implementation plans.
- Define scalable, secure, reliable, and cost-effective architectures for data ingestion, transformation, storage, governance, orchestration, analytics, and data consumption.
- Remain hands-on in engineering work, including designing data pipelines, reviewing code, building proof of concepts, resolving complex technical issues, and establishing engineering patterns.
- Architect and implement batch, real-time, streaming, and event-driven data solutions as appropriate for client needs.
- Design modern cloud data platforms using technologies such as Snowflake, Databricks, Microsoft Fabric, Azure Data Factory, AWS Glue, Amazon Redshift, BigQuery, or equivalent platforms.
- Lead the development of robust ETL/ELT pipelines, data models, data APIs, semantic layers, and data products.
- Establish data engineering standards for code quality, testing, CI/CD, observability, metadata management, data lineage, documentation, security, and production support.
- Drive adoption of DataOps practices, infrastructure as code, automated testing, deployment pipelines, monitoring, and incident-management processes.
- Partner with data architects, data scientists, analysts, application architects, security teams, and business stakeholders to ensure solutions are aligned to enterprise architecture and business outcomes.
- Present technical recommendations, architecture options, delivery status, risks, and strategic roadmaps to both technical and executive audiences.
- Lead client-facing demonstrations, workshops, steering-committee updates, and technical presentations.
- Mentor senior, mid-level, and junior data engineers; provide technical coaching, career guidance, design feedback, and hands-on support.
- Lead and influence cross-functional delivery teams, including onshore/offshore engineers, architects, analysts, and client technical resources.
- Participate in project estimation, staffing, delivery planning, risk management, solution scoping, and proposal development.
- Support pre-sales and business-development activities, including solutioning, client presentations, technical discovery, RFP responses, estimates, and statement-of-work development.
- Stay current on emerging data, cloud, AI, governance, and analytics technologies; evaluate where they provide meaningful business value for clients.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; equivalent professional experience may be considered.
- 10+ years of progressive experience in data engineering, data warehousing, data integration, data architecture, or related technical disciplines.
- 3+ years of experience in a technical leadership, lead engineer, solution architect, staff engineer, principal engineer, or consulting leadership capacity.
- Demonstrated experience architecting and delivering enterprise-scale data platforms and data integration solutions.
- Strong hands-on expertise in SQL and at least one modern programming language, preferably Python, Scala, Java, or C#.
- Strong experience with ETL/ELT design, data pipeline development, data transformation frameworks, orchestration, and workflow automation.
- Experience with one or more cloud providers: Microsoft Azure, AWS, or Google Cloud Platform.
- Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies.
- Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools.
- Knowledge of distributed data-processing technologies such as Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable platforms.
- Experience designing both batch and near-real-time or streaming data solutions.
- Strong understanding of dimensional modeling, data vault, normalized data models, lakehouse architectures, data lake architectures, and data warehouse design principles.
- Experience implementing data quality, data validation, monitoring, lineage, metadata, governance, and security controls.
- Working knowledge of DevOps and DataOps practices, including Git-based source control, CI/CD, automated testing, deployment automation, and infrastructure as code.
- Strong understanding of cloud security principles, identity and access management, encryption, secrets management, and role-based access controls.
- Proven ability to lead architecture discussions and make well-reasoned technical tradeoffs involving performance, scalability, reliability, maintainability, security, and cost.
- Excellent verbal, written, and presentation skills, with the ability to explain technical concepts clearly to business stakeholders and executive audiences.
- Experience in a consulting, professional services, systems integrator, or client-facing delivery environment.
- Experience designing data platforms that support AI, machine learning, generative AI, retrieval-augmented generation, feature stores, vector databases, or advanced analytics workloads.
- Certifications in AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, or other relevant data technologies.
- Experience with master data management, data cataloging, data governance, privacy, regulatory compliance, or data stewardship programs.
- Experience with tools such as Collibra, Alation, Microsoft Purview, Unity Catalog, Informatica, Monte Carlo, Great Expectations, or similar governance and observability platforms.
- Experience with Salesforce, SAP, ERP, CRM, finance, supply-chain, healthcare, retail, manufacturing, or other enterprise operational data domains.
- Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms.
- Experience with containerization and cloud-native technologies such as Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi.
- Prior experience contributing to proposals, estimates, statements of work, or technical sales pursuits.
- Experience managing or leading distributed onshore/offshore delivery teams.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Houston or Dallas, TX
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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