Data Engineer, Data Platforms

Overview

Build, transition, and operate data pipelines on Databricks and AWS platforms. Support governed lakehouse delivery, data onboarding, mastering integration, technical guidance, and AI-assisted engineering.

What you'll do

• Transition existing pipelines to the target enterprise data platform.
• Build and optimize batch and streaming ingestion and transformation pipelines.
• Implement testing, deployment, monitoring, observability, and operational support practices.
• Apply AWS security patterns using IAM, encryption, and platform guardrails.
• Support dataset onboarding, reusable templates, documentation, and runbooks.
• Integrate platform datasets with data mastering and maintain quality and reconciliation controls.
• Review designs and code while guiding engineering peers and global delivery teams.

What you'll need

• 5–7+ years of experience in data engineering, data platforms, or related technical domains.
• Hands-on experience building and operating batch or streaming data pipelines.
• Experience with Databricks platforms and lakehouse architectures.
• Strong familiarity with AWS S3, Glue, Lambda, Lake Formation, Kinesis, and IAM.
• Working knowledge of Delta Lake, Apache Iceberg, and Databricks Unity Catalog.
• Experience using AI-assisted engineering tools such as Claude, GitHub Copilot, or LLM-based development features.
• Ability to validate AI-generated outputs and apply secure usage practices.

Nice to have

• Experience with enterprise onboarding frameworks and reusable ingestion patterns.
• Familiarity with data cataloging, metadata management, and governed data products.
• Exposure to data mastering or MDM workflows and golden records.
• Experience in regulated environments with governance and auditability requirements.
• Databricks or AWS certifications.

Details

• Location: Hyderabad, Telangana, India.