Data Engineer with AWS Databrick

Work Mode: Hybrid (3 days WFO)
Locations: Bangalore, Noida, Pune, Mumbai, Hyderabad (Candidates must be in Accion cities to collect assets and attend in-person meetings as required).

Key Requirements:
Technical Skills:

Databricks Expertise:

5+ years of hands-on experience in data engineering/ETL using Databricks on AWS/Azure cloud infrastructure.
Proficiency in Delta Lake, Unity Catalog, Delta Sharing, Delta Live Tables (DLT), MLflow, and Databricks SQL.
Experience with Databricks CI/CD tools (e.g., BitBucket, GitHub Actions, Databricks CLI).
Data Warehousing & Engineering:

Strong understanding of data warehousing concepts (Dimensional, SCD2, Data Vault, OBT, etc.).
Proven ability to implement highly performant data ingestion pipelines from multiple sources.
Experience integrating end-to-end Databricks pipelines to ensure data quality and consistency.
Programming:

Strong proficiency in Python and SQL.
Basic working knowledge of API or stream-based data extraction processes (e.g., Salesforce API, Bulk API).
Cloud Technologies:

Preferred experience with AWS services (e.g., S3, Athena, Glue, Lambda).
Power BI:

3+ years of experience in Power BI and data warehousing for root cause analysis and business improvement opportunities.
Additional Skills:

Working knowledge of Data Management principles (quality, governance, security, privacy, lifecycle management, cataloging).
Nice to have: Databricks certifications and AWS Solution Architect certification.
Nice to have: Experience with building data pipelines from business applications like Salesforce, Marketo, NetSuite, Workday, etc.
Responsibilities:
Develop, implement, and maintain highly efficient ETL pipelines on Databricks.
Perform root cause analysis and identify opportunities for data-driven business improvements.
Ensure quality, consistency, and governance of all data pipelines and repositories.
Work in an Agile/DevOps environment to deliver iterative solutions.
Collaborate with cross-functional teams to meet business requirements.
Stay updated on the latest Databricks and AWS features, tools, and best practices.
Work Schedule:
Regular: 11:00 AM to 8:00 PM.
Flexibility is required for project-based overlap.
Interested candidates should share their resumes with the following details:
Current CTC
Expected CTC
Preferred Location: Bangalore, Noida, Pune, Mumbai, Hyderabad
Notice Period
Contact Information: