Data Architecture Specialist

2 days ago

Vijayawada, Andhra Pradesh, India beBeeDataEngineer Full time ₹ 14,00,000 - ₹ 20,10,000
About the Job

We are seeking a skilled professional to fill the role of Data Engineer in our organization.

  • Job Summary:
  • The ideal candidate will have hands-on experience in building and automating data pipelines, managing multi-environment deployments, and working with modern DevOps/configuration management tools.

Responsibilities:

  • Design and Implement Continuous Integration/Continuous Deployment Pipelines:
  • Create efficient and reliable CI/CD pipelines using GitHub Actions or equivalent tools to streamline code integration and deployment.
  • Configure and Maintain GitHub Branch Protection Rules and Workflows:
  • Establish and enforce robust branch protection rules and workflows to ensure smooth code integration and deployment.
  • Build, Optimize, and Debug Spark Jobs in Databricks:
  • Develop, optimize, and debug Spark jobs in Databricks for large-scale data processing.
  • Automate Databricks Deployments:
  • Automate Databricks deployments using Databricks Asset Bundles (DABs) or similar frameworks to enhance efficiency.
  • Develop Robust Data Pipelines:
  • Design, develop, and maintain robust data pipelines using Python and SQL to ensure accurate and timely data delivery.
  • Implement Unit Testing and Quality Checks:
  • Implement unit testing, validation, and quality checks for data workflows to guarantee reliability.
  • Manage Multi-Environment Deployments:
  • Ensure seamless multi-environment deployments (Dev, Stage, Prod) to guarantee consistency and reliability.
  • Troubleshoot Configuration Issues:
  • Identify and resolve configuration or syntax issues in YAML and related files to prevent downtime.
  • Maintain Critical Databricks Notebooks:
  • Guarantee critical Databricks notebooks run reliably to ensure business continuity.
  • Migrate Legacy Reports:
  • Transform legacy reports into modern, self-serve dashboards (Snowflake, Tableau, Power BI) to enhance user experience.
  • Collaborate with Cross-Functional Teams:
  • Foster strong partnerships with cross-functional teams to understand needs and deliver actionable insights and reporting they can trust.
  • Implement Data Governance:
  • Establish data contracts, quality checks, and documentation to ensure long-term reliability and consistency.

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