
Senior Data Engineer
3 days ago
Celebal is looking for Data Engineer/Senior Data Engineer.
Company Profile
- Celebal Technologies a Premier Microsoft Azure partner and have been recently funded by Norwest Venture Capital. Celebal Technologies is a premier software services company in the field of Data Science, Big Data, Enterprise Cloud & Automation. Established in 2016, in this short span of time we grew to headcount of 2200+ We help in achieving a competitive advantage with intelligent data solutions, built using cutting-edge technology.
Key Responsibilities:
• Lead the implementation of data ingestion pipelines, ensuring optimized data flow and transformation logic.
• Oversee and guide the migration of DBT ETL scripts, rewriting or optimizing SQL and PySpark code for Databricks.
• Expertise in DBT, SQL Server, Synapse (T-SQL, performance tuning) and data migration to cloud platforms.
• In-depth knowledge of Databricks, Spark, Delta Lake, and integration with Azure services.
• Design and implement reusable frameworks for data transformations, logging, and error handling in Databricks.
• Strong understanding of cloud-based architecture for data lakes, data warehouses, and scalability.
• Expertise in Azure Data Factory (ADF), Synapse Analytics, and Azure Blob Storage integration with Databricks.
• Experience in implementing and managing Medallion architecture (Bronze, Silver, Gold) in Databricks.
• Optimize Spark configurations, cluster sizing, and execution strategies for performance improvements.
• Conduct code reviews to ensure adherence to best practices, performance optimizations, and security guidelines.
• Debug and troubleshoot issues related to data ingestion, transformation, and job failures in Databricks.
• Collaborate with data engineers and analysts to ensure transformed data meets business requirements and reporting needs.
• Implement robust logging and monitoring using tools such as Datadog, Prometheus, or Azure Monitor.
• Work closely with cloud and DevOps teams to enable infrastructure as code (IaC) for Databricks workspace management.
• Provide guidance on version control strategies, branching, and release management for data pipeline
• Act as a bridge between the Solution Architect and the development team, ensuring seamless implementation.
• Ensure data quality by implementing validation checks, data reconciliation, and automated data profiling.
• Strong collaboration and communication skills for leading cross-functional teams and reporting to stakeholders.
• Document all technical aspects, including ETL flows, DevOps workflows, and migration steps for knowledge sharing.
• Mentor junior engineers, conduct knowledge-sharing sessions, and enforce coding standards across the team.
Technical Skills:
• Expertise in Databricks, Spark, PySpark, Delta Lake, and SQL
• Strong hands-on experience with DBT, SQL Server, and T-SQL performance tuning
• Proficiency in Azure cloud services (Data Factory, Synapse, Blob Storage, etc.)
• CI/CD implementation for data pipelines using Azure DevOps, Terraform, or GitHub Actions
• Experience with Medallion architecture and scalable data processing solutions
• Monitoring and troubleshooting using Datadog, Prometheus, or Azure Monitor
• Experience in DevOps, automation, and infrastructure as code (IaC) for Databricks management
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