Associate Data Engineer
Listed on 2026-01-12
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IT/Tech
Data Engineer
Baker Tilly is a leading advisory, tax and assurance firm, providing clients with a genuine coast‑to‑coast and global advantage in major regions of the U.S. and in many of the world’s leading financial centers – New York, London, San Francisco, Los Angeles, Chicago and Boston. Baker Tilly Advisory Group, LP and Baker Tilly US, LLP provide professional services through an alternative practice structure in accordance with the AICPA Code of Professional Conduct and applicable laws, regulations and professional standards.
Baker Tilly US, LLP is a licensed independent CPA firm that provides attest services to its clients. Baker Tilly Advisory Group, LP and its subsidiary entities provide tax and business advisory services to their clients. Baker Tilly Advisory Group, LP and its subsidiary entities are not licensed CPA firms.
Baker Tilly Advisory Group, LP and Baker Tilly US, LLP, trading as Baker Tilly, are independent members of Baker Tilly International, a worldwide network of independent accounting and business advisory firms in 141 territories, with 43,000 professionals and a combined worldwide revenue of $5.2 billion.
Baker Tilly is an equal opportunity / affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, gender identity, sexual orientation, or any other legally protected basis, in accordance with applicable federal, state or local law.
Job TitleAssociate Data Engineer
Job DescriptionAs a Senior Consultant – Associate Data Engineer you will design, build, and optimize modern data solutions for our mid‑market and enterprise clients. Working primarily inside the Microsoft stack (Azure, Synapse, and Microsoft Fabric), you will transform raw data into trusted, analytics‑ready assets that power dashboards, advanced analytics, and AI use cases. You’ll collaborate with solution architects, analysts, and client stakeholders while sharpening both your technical depth and consulting skills.
Key Responsibilities- Data Engineering:
Develop scalable, well‑documented ETL/ELT pipelines using T‑SQL, Python, Azure Data Factory/Fabric Data Pipelines, and Databricks; implement best‑practice patterns for performance, security, and cost control. - Modeling & Storage:
Design relational and lakehouse models; create Fabric One Lake shortcuts, medallion‑style layers, and dimensional/semantic models for Power BI. - Quality & Governance:
Build automated data‑quality checks, lineage, and observability metrics; contribute to CI/CD workflows in Azure Dev Ops or Git Hub. - Client Delivery:
Gather requirements, demo iterative deliverables, document technical designs, and translate complex concepts to non‑technical audiences. - Continuous Improvement:
Research new capabilities, share findings in internal communities of practice, and contribute to reusable accelerators. Collaborate with clients and internal stakeholders to design and implement scalable data engineering solutions.
- Education – Bachelor’s in Computer Science, Information Systems, Engineering, or related field (or equivalent experience)
- Experience – 2–3 years delivering production data solutions, preferably in a consulting or client‑facing role.
- Technical
Skills:- Strong T‑SQL for data transformation and performance tuning.
- Python for data wrangling, orchestration, or notebook‑based development.
- Hands‑on ETL/ELT with at least one Microsoft service (ADF, Synapse Pipelines, Fabric Data Pipelines).
- Project experience with Microsoft Fabric (One Lake, Lake houses, Data Pipelines, Notebooks, Warehouse, Power BI Direct Lake) preferred.
- Familiarity with Databricks, Delta Lake, or comparable lakehouse technologies preferred.
- Exposure to Dev Ops (YAML pipelines, Terraform/Bicep) and test automation frameworks preferred.
- Experience integrating SaaS/ERP sources (e.g., Dynamics 365, Workday, Costpoint) preferred.
Mid‑Senior level
Employment TypeFull‑time
Job FunctionInformation Technology
IndustryAccounting
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