Senior Data Architect

7 days ago

Aurangabad, Maharashtra, India beBeeData Full time ₹ 8,00,000 - ₹ 16,00,000

We are seeking a seasoned Data Engineer to join our team, focused on designing and implementing scalable data pipelines, automating deployments, and collaborating with cross-functional teams.

Key Responsibilities
  • Data Pipeline Development: Design, implement, and manage continuous integration and deployment pipelines using GitHub Actions or equivalent tools.
  • Pipeline Optimization: Configure and maintain GitHub branch protection rules and workflows to ensure smooth code integration and deployment.
  • Databricks Integration: Build, optimize, and debug Spark jobs in Databricks for large-scale data processing.
  • Automation and Deployment: Automate Databricks deployments using Databricks Asset Bundles (DABs) or similar frameworks.
  • Data Workflow Development: Develop, test, and maintain robust data pipelines using Python and SQL.
  • Quality Assurance: Implement unit testing, validation, and quality checks for data workflows.
  • Deployment Management: Manage multi-environment deployments (Dev, Stage, Prod) ensuring reliability and consistency.
  • Configuration Management: Write and maintain configuration files (YAML, JSON) for workflows, pipelines, and automation.
  • Troubleshooting: Troubleshoot and resolve configuration or syntax issues in YAML and related files.
  • Business Continuity: Keep critical Databricks notebooks running reliably to ensure business continuity.
  • Legacy Report Migration: Migrate legacy reports into modern, self-serve dashboards (Snowflake, Tableau, Power BI).
  • Cross-Functional Collaboration: Partner with cross-functional teams to understand needs and deliver data models, insights, and reporting they can trust.

What We're Looking For:

  • Technical Skills: Strong skills in SQL, Databricks (Spark), and Python/R.
  • CI/CD Experience: Strong knowledge of GitHub and CI/CD practices (branch protection, GitHub Actions workflows).
  • Unit Testing: Experience in implementing unit tests and quality checks in data workflows.
  • Automation Tools: Knowledge of Databricks Asset Bundles (DABs) or similar automation tools.
  • Configuration Management: Familiarity with YAML configuration management, debugging, and error resolution.
  • Problem-Solving: Strong problem-solving and debugging skills in data engineering workflows.
  • Cloud Data Warehouse: Experience with Snowflake or another cloud data warehouse.
  • Dashboards: Hands-on experience with Tableau/Power BI dashboards and a good sense for usability.

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