Senior Data Engineer / ML Platform Engineer (Azure Databricks & GenAI)

Job Description

Job Description

Tekfortune is a fast-growing consulting firm specialized in permanent, contract & project-based staffing services for world s leading organizations in a broad range of industries. In this quickly changing economic landscape, virtual recruiting and remote work are critical for the future of work. To support the active project demands and skills gaps, our staffing experts can help you find the best job for you.

Senior Data Engineer / ML Platform Engineer (Azure Databricks & GenAI)
Location: Onsite Warren, MI or Austin, TX 4 days per week
6 Months Contract to Hire

Summary
We are augmenting an internal team with contract contractors who have strong Azure
Databricks and ML data platform skills. Our staff already owns platform standards, Unity Catalog governance, and architecture; we need additional capacity to deliver lakehouse pipelines, catalogued engineering and enterprise datasets, and GenAI-ready data
products (embeddings, retrieval, batch enrichment) in parallel with other priorities. Assignments may span multiple programs not a single fixed product so candidates should be comfortable ramping on new domains and codebases quickly.

Responsibilities

• Design and build production data pipelines on Databricks (PySpark/SQL, Delta Lake, Unity Catalog, Workflows/Jobs) with idempotency, testing, monitoring, and clear lineage.
• Model bronze / silver / gold layers and data contracts (schemas, SLAs, quality checks) for analytics and downstream applications.
• Develop ML-oriented data products: feature stores or curated tables, embedding generation, chunking/indexing for RAG, batch classification/enrichment, and evaluation of retrieval/data quality.
• I ntegrate with Azure services (ADLS Gen2, Key Vault, managed identities, private connectivity) following enterprise security and compliance patterns.
• Partner with application and ML teams to expose stable APIs, tables, and volumes that p ower agentic workflows (tool-backed assistants, multi-step orchestration) without owning full UI or real-time serving unless scoped.
• D ocument data dictionaries, runbooks, and handoff materials; participate in code review and agile ceremonies with full-time staff.

Required qualifications

• 5 years in data engineering, including 2 years production Databricks on Azure.
• S trong Python (PySpark, pandas); SQL; experience operationalizing jobs at scale.
• Hands-on Delta Lake and Unity Catalog (schemas, grants, environments, promotion patterns).
• E xperience building pipelines that feed ML/GenAI use cases: embeddings, vector or hybrid search inputs, labeled datasets, batch inference outputs.
• Git, CI-friendly repo layout (notebooks packages), unit/integration testing for data pipelines.
• Strong communication; effective in staff augmentation models (embedded with internal l eads, shared standards).

Preferred qualifications

• GenAI / agentic systems: RAG design, retrieval evaluation, metadata for grounding, guardrails-aware data prep.
• Multi-source integration: documents, PLM/BOM-style structured data, files in object storage, APIs, spreadsheets normalized into a catalog.
• Exposure to containerized or microservice backends (for collaboration with app teams, not primary ownership).

Nice to have (role-dependent)

• MLOps on Databricks (Model Serving, Feature Serving, experiment tracking).
• Stream or near-real-time ingestion (Structured Streaming, event-driven triggers).
• Infrastructure-as-code literacy (Terraform/Bicep) often owned internally; ability to consume outputs is enough.
• Graph or highly relational domains (requirements traceability, product structure, hierarchies).
• Automotive or complex manufacturing data (helpful, not required).

What we provide

• Platform expertise, Databricks/Azure standards, architecture review, and access to tooling and repos per assignment.
• Clear priorities from product/engineering owners; expectations to align with existing team patterns rather than invent a separate stack.

For more information and other jobs available please contact our recruitment team at View email address on ziprecruiter.com . To view all the jobs available in the USA and Asia please visit our website at .