Senior Consultant | Cloud Integration | Azure Data Factory (ADF)

Description: Job Title: Data Engineer Work Location : Ann ArborMI48105 Vendor Rate: *** - *** Contract duration: 6 Target Start Date: 07 Sep 2026 Does this position require Visa independent candidates only? Yes **Full On-site (4days WFO/ week)** Job Details: Must Have Skills: Databricks, ADF, PySpark Nice to have skills: SQL, Gen AI, Control-M Detailed Job Description Key Responsibilities Design, build, and maintain data pipelines using Azure Databricks Perform data ingestion, transformation, and processing for enterprise data platforms Work closely with onsite client teams and stakeholders to understand data requirements Support data engineering workloads aligned to DNA (Data & Analytics) programs Collaborate with offshore teams, as applicable, to ensure end‑to‑end delivery Required Technical Skills Databricks – strong hands‑on experience (mandatory) Experience working with Unity Catalog, *** Lake, DLT Pipelines, Pyspark, SQL, Python, Databricks Rest API, Version Control (Git/Gitlab), Data Governance Azure Data Engineering stack Azure Databricks Azure data services(ADF, Key Vault, ADLS, Blob storage) Strong foundation in Data Engineering concepts (ETL/ELT, distributed processing) Ability to work independently in an onsite client environment MUST have Willingness to relocate or work onsite in Ann Arbor, MI Candidate need to work 4 days/week from client HQ Ability to join quickly due to urgent client demand Strong communication skills for onsite coordination Minimum Years Of Experience 8-10 years Certifications Needed :No Top 3 responsibilities you would expect the Subcon to shoulder and execute Provide strategic Input architectural guidance for new implementation areas ensuring a robust foundation for migration and setup projects Interview Process (Is face to face required?) No Any additional information you would like to share about the project specs/ nature of work Custom Fields: Name: Intake Call Requested Value: true Name: Intake Call Completed Value: false