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Data Engineering Manager

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Hybrid

Data Engineering Manager

Naukri E Hire Campaign

Data Engineering Manager

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonDatabricksAWSPySparkComplianceAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

10 September 2026

What they need


Company - Optum

Exp - 7-14 yrs

Location - Bangalore

Skills - Data Engineering, Python programming, SQL programming, Pyspark programming, Databricks, Azure / AWS / GCP, End to End Pipeline Build (Extract, Transform, Load), Basic Data Modeling, Health care domain exposure, GenAI Exposure

Primary Responsibilities:

  • Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines
  • Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
  • Analyze business and customer requirements and translate them into technical data solutions
  • Identify and resolve non-standard data challenges and moderately complex engineering problems
  • Develop and maintain data models, data quality frameworks, and validation processes
  • Collaborate with data analysts, data scientists, product teams, and business stakeholders to deliver trusted data assets
  • Monitor and optimize pipeline performance, reliability, scalability, and cost efficiency
  • Support cloud-based data platforms and data warehouse/lakehouse environments
  • Implement data governance, security, lineage, and compliance standards across data assets
  • Create technical documentation, design specifications, and operational procedures
  • Provide technical guidance and knowledge sharing to junior engineers and team members
  • Participate in code reviews and promote engineering best practices for development, testing, and deployment
  • Troubleshoot production issues, perform root-cause analysis, and implement sustainable solutions
  • Contribute to automation, CI/CD processes, and continuous improvement initiatives across the data ecosystem

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