Data Engineer

6 days ago

Bengaluru Hyderabad Pune, India Brillio Full time ₹ 8,00,000 - ₹ 24,00,000 per year

About the Role

We are seeking a Build & Deploy Engineer with strong expertise in ETL tools, scripting, and databases to manage the build, release, and deployment lifecycle of data integration workflows. The ideal candidate will have hands-on experience with DataStage, SSIS, IICS, Python, Unix scripting, and SQL deployments, ensuring smooth development-to-production transitions and reliable delivery of data pipelines.

Key Responsibilities

  • Build, configure, and deploy ETL workflows using DataStage, SSIS, and IICS.
  • Automate deployment and operational processes using Python and Unix shell scripting.
  • Deploy SQL scripts, stored procedures, and schema changes to databases (SQL Server, Oracle, etc.).
  • Collaborate with developers, data engineers, and operations teams to manage build promotions across environments.
  • Troubleshoot deployment failures, perform root cause analysis, and ensure quick resolution.
  • Implement CI/CD pipelines, version control, and build automation best practices.
  • Maintain comprehensive documentation for build, release, and deployment processes.
  • Ensure data security, compliance, and performance optimization during deployments.

Required Skills & Qualifications

  • Strong experience with ETL tools: DataStage, SSIS, IICS.
  • Proficiency in Python and Unix shell scripting for automation.
  • Hands-on experience deploying SQL scripts, schema changes, and database objects.
  • Solid understanding of build & release management and deployment automation.
  • Experience with version control systems (Git, GitHub, GitLab, Bitbucket).
  • Strong problem-solving, debugging, and troubleshooting abilities.
  • Ability to work effectively in cross-functional, collaborative environments.

Preferred Skills

  • Familiarity with DevOps tools (Jenkins, Azure DevOps, Bamboo) and automated pipelines.
  • Knowledge of data warehousing, SQL optimization, and performance tuning.
  • Exposure to containerization (Docker, Kubernetes) for deployment automation.

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