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.
Pittsburgh, PA, United States
Live, first seen by us 55 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design and implement scalable data architecture, pipelines and modeling for the BigQuery warehouse
Own end-to-end ETL/ELT architecture: ingestion, transformation, modeling and orchestration
Translate business goals into data products and analytical solutions with the BI team
Enforce data integrity, security, governance and quality standards
Mentor data engineers and cross-functional teams technically
Design and implement scalable data architecture, pipelines, and modeling strategies that power our enterprise data warehouse on GCP (BigQuery).
Own the end-to-end ETL/ELT architecture, including ingestion, transformation, modeling, and orchestration.
Partner with business leaders and the BI team to translate strategic goals into high-quality data products and analytical solutions.
Ensure data integrity and security by adhering to and upholding data governance, quality standards, and architectural best practices.
Serve as a technical mentor and guide to data engineers and cross-functional teams.
Experience: 10+ years in data engineering, data architecture, or data analytics roles, with a minimum of 3 years specifically dedicated to a Data Architect position. Candidates must demonstrate a proven history of designing and delivering high-performance, enterprise-scale data strategies that bridge the gap between technical infrastructure and strategic business outcomes.
Communication: Ability to engage with both technical and non-technical stakeholders to translate complex requirements into impactful solutions.
- GCP Ecosystem: Strong expertise in Google Cloud Platform, specifically BigQuery, Cloud Composer (Airflow), Dataflow, Pub/Sub, Cloud Storage, Slot Reservations/Workload Management. - Languages: Expert-level SQL is required; Python proficiency is a strong plus for custom operators and advanced data processing. - Governance: Solid understanding of data governance, metadata management, security, and compliance in cloud environments.
- Industry Knowledge: Background in the retail industry or high-volume transactional environments. - Emerging Technology: Familiarity with or vision for integrating Generative AI into data engineering workflows (e.g., using LLMs for SQL generation, automated metadata documentation, or synthetic data creation). Perks: Why You’ll Love it Here
What You’ll Do: - Architectural Blueprinting: Design and implement scalable data architecture, pipelines, and modeling strategies that power our enterprise data warehouse on GCP (BigQuery). - ETL/ELT Ownership: Own the end-to-end ETL/ELT architecture, including ingestion, transformation, modeling, and orchestration.
- Enterprise Data Modeling: Expertise in designing and implementing enterprise data warehouses, including star/snowflake schemas and dimensional modeling techniques in a Medallion architecture. - Modern Architecture Standards: Proven experience implementing Lakehouse patterns (specifically using BigQuery and open table formats like Iceberg), Data Mesh (domain-driven design), and real-time streaming architectures. - GCP Ecosystem: Strong expertise in Google Cloud Platform, specifically BigQuery, Cloud Composer (Airflow), Dataflow, Pub/Sub, Cloud Storage, Slot Reservations/Workload Management.
- Modern Architecture Standards: Proven experience implementing Lakehouse patterns (specifically using BigQuery and open table formats like Iceberg), Data Mesh (domain-driven design), and real-time streaming architectures. - GCP Ecosystem: Strong expertise in Google Cloud Platform, specifically BigQuery, Cloud Composer (Airflow), Dataflow, Pub/Sub, Cloud Storage, Slot Reservations/Workload Management. - Languages: Expert-level SQL is required; Python proficiency is a strong plus for custom operators and advanced data processing.
- Platform Thinking & Strategy: Proven ability to balance immediate business delivery with long-term architectural health; a strategic thinker who can navigate complex stakeholder requirements to build scalable, future-proof data platforms. - BI Tooling: Experience working with BI tools (e.g., Tableau, Looker, AtScale, Databricks) to support self-service and enterprise reporting. - Communication: Ability to engage with both technical and non-technical stakeholders to translate complex requirements into impactful solutions.
Get to Know the Role: We are seeking an experienced Data Architect to lead the design and implementation of our enterprise data architecture and ETL frameworks supporting our modern data warehouse in Google Cloud Platform (GCP). You will play a pivotal role in shaping our data strategy, ensuring scalable, reliable, and secure solutions that empower business users and analysts to deliver actionable insights. This role sits at the intersection of architecture, engineering, and business, collaborating closely with business stakeholders, product managers, and the business intelligence team to enable strategic analytics and decision-making across the organization. What You’ll Do:
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$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.
Day 55
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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.
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.
Title: Data Architect
Reports To: Director - Data Engineering
Location: Pittsburgh, PA or New York, NY
American Eagle is a youth culture brand grounded in denim. Our purpose extends beyond making the best jeans–we embrace self expression, culture, optimism and connection. Through the brand platform Live Your Life, we empower our community to be who they want to be all while wearing the clothes that make them most confident.
Get to Know the Role:
We are seeking an experienced Data Architect to lead the design and implementation of our enterprise data architecture and ETL frameworks supporting our modern data warehouse in Google Cloud Platform (GCP). You will play a pivotal role in shaping our data strategy, ensuring scalable, reliable, and secure solutions that empower business users and analysts to deliver actionable insights. This role sits at the intersection of architecture, engineering, and business, collaborating closely with business stakeholders, product managers, and the business intelligence team to enable strategic analytics and decision-making across the organization.
What You’ll Do:
What You Bring:
Nice to Have:
Perks: Why You’ll Love it Here
Pay/Benefits Information:
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Pittsburgh, PA, United States
- Casual dress code - Hybrid schedule - FOMO events (Exciting company-wide events)
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We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting