Sr. Data Engineer

Location : Preferred Hyd or Bangalore but can be remote for right candidate.

Exp: 8-10+ years

Skillset

• Design and implement robust, production-grade pipelines using Python, Spark SQL, and Airflow to process high-volume file-based datasets (CSV, Parquet, JSON).
• Own the full lifecycle of core pipelines — from file ingestion to validated, queryable datasets — ensuring high reliability and performance.
• Build resilient, idempotent transformation logic with data quality checks, validation layers, and observability.
• Refactor and scale existing pipelines to meet growing data and business needs.
• Tune Spark jobs and optimize distributed processing performance.
• Implement schema enforcement and versioning aligned with internal data standards.
• Collaborate deeply with Data Analysts, Data Scientists, Product Managers, Engineering, Platform, SMEs, and AMs to ensure pipelines meet evolving business needs.
• Monitor pipeline health, participate in on-call rotations, and proactively debug and resolve production data flow issues.
• Contribute to the evolution of our data platform — driving toward mature patterns in observability, testing, and automation.
• Build and enhance streaming pipelines (Kafka, SQS, or similar) where needed to support near-real-time data needs.
• Help develop and champion internal best practices around pipeline development and data modeling.

Experience

• 8-10 years of experience as a Data Engineer (or equivalent), building production-grade pipelines.
• Strong expertise in Python, Spark SQL, and Airflow.
• Experience processing large-scale file-based datasets (CSV, Parquet, JSON, etc) in production environments.
• Experience mapping and standardizing raw external data into canonical models.
• Familiarity with AWS (or any cloud), including file storage and distributed compute concepts.
• Ability to work across teams, manage priorities, and own complex data workflows with minimal supervision.
• Strong written and verbal communication skills — able to explain technical concepts to non-engineering partners.
• Comfortable designing pipelines from scratch and improving existing pipelines.
• Experience working with large-scale or messy datasets (healthcare, financial, logs, etc.).
• Experience building or willingness to learn streaming pipelines using tools such as Kafka or SQS.
• Bonus: Familiarity with healthcare data (837, 835, EHR, UB04, claims normalization).

Please share your updated resume with below details:

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Any offer in hand or in pipeline:

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Job Type: Full-time

Pay: ₹3,000,000.00 - ₹3,500,000.00 per year

Benefits:

• Health insurance