Data Engineer

firstPRO US; Virginia; On-site; USD 140,000 - 190,000; Full time

Job summary

firstPRO US is building a modern, enterprise cloud data and AI platform for a financial services client in the United States. Data Engineers will design and deploy robust ELT pipelines on Snowflake/dbt, modernize legacy workflows, and ensure data quality and observability.

Senior engineers will drive technical design, mentor teammates, and lead complex migration and modeling workstreams in a distributed environment. Collaboration with onshore and offshore teams is essential.

Qualifications

• 5+ years of hands-on data engineering experience building production data pipelines and warehouse models, with 8+ years for senior candidates.
• Deep experience with Snowflake: warehouse objects, roles, tasks/streams, and cost tuning.
• dbt proficiency: layered models, incremental builds, tests, and CI workflows.
• Strong SQL and Python for data ingestion, APIs, and automation.
• Experience with medallion/layered cloud architectures, conformed dimensions, and data contracts.
• Proven Git, automated testing, CI/CD, and pipeline observability.
• Clear written and verbal communication for technical design notes and PR reviews.

Responsibilities

• Build and model ELT pipelines using Snowflake and dbt across a medallion architecture.
• Modernize legacy analytics workflows (Alteryx, SSIS) and implement parity verification.
• Embed data quality as code and observability into development cycles.
• Follow Git-based workflows, CI/CD, peer reviews, and documentation.
• Profile performance, optimize warehouse sizing and clustering, manage Snowflake compute.
• Collaborate with onshore and offshore teams to deliver evidence-based results.

Skills

Snowflake

dbt

SQL

Python

Architecture

Engineering Best Practices

Communication

Tools

Airflow

Dagster

Git

CI/CD

Job description

We are seeking Data Engineers and Senior Data Engineers to help build a modern, enterprise cloud data and AI platform for a leading financial services organization. This multi-year initiative replaces legacy analytics workflows with governed, reusable data products on Snowflake and dbt, transitioning the business from retrospective reporting to data-driven decisioning.

You will report to the Director of Data Engineering and work in a collaborative, distributed engineering environment. Senior candidates will also drive technical design, mentor team members, and lead complex migration and modeling workstreams.

Key Responsibilities

• Build & Model: Design and deploy robust ELT pipelines using Snowflake and dbt across a governed medallion architecture (bronze/silver/gold, conformed entities, and semantic layers) for BI, API, and ML/AI consumers.
• Modernize & Migrate: Reverse-engineer legacy analytics workflows (e.g., Alteryx, SSIS, stored procedures), re-implement them cleanly in Snowflake/dbt, and establish parity verification.
• Data Quality & Testing: Embed data quality as code (dbt tests, source freshness, reconciliation checks, and observability) directly into development cycles.
• Software Engineering Discipline: Follow Git-based workflows, automated CI/CD, peer code reviews, environment promotion, and detailed documentation.
• Performance & Cost Optimization: Profile query performance, optimize warehouse sizing and clustering, and practice disciplined Snowflake compute management.
• Evidence-Based Delivery: Build against clear design specifications, produce comprehensive developer verification evidence, and collaborate across onshore and offshore partner teams.

Qualifications

• Experience: 5+ years of hands-on data engineering experience building production data pipelines and warehouse models (8+ years with demonstrated technical leadership and mentoring for Senior level).
• Core Stack:
• Snowflake: Deep experience with warehouse and database objects, role-based access, tasks/streams, and performance/cost tuning at scale.
• dbt: Strong production experience structuring layered models, incremental builds, custom macros, schema tests, and CI workflows.
• SQL & Python: Advanced SQL skills (complex transformations, window functions, tuning) combined with solid Python for ingestion utilities, APIs, and automation.
• Architecture: Practical experience building within medallion/layered cloud data architectures, conformed dimensions, and data contracts.
• Engineering Best Practices: Proven track record with Git, automated testing, CI/CD, and robust pipeline observability.
• Communication: Clear written and verbal communication for technical design notes, pull request reviews, and cross-functional coordination.

Preferred Qualifications

• Experience working in financial services, banking, fintech, or other regulated environments handling sensitive data.
• Background in legacy migrations (Alteryx, SSIS, SAS) with rigorous parity testing.
• Experience with orchestration tools (Airflow, Dagster), CDC pipelines, data catalogs, or BI/semantic layers.