Job Description
Roles & Responsibilities
• Develop Databricks notebooks, jobs, and workflows to replicate and enhance DB2/Guidewire-based pipelines and transformations.
• Implement Delta Lake tables and patterns (bronze/silver/gold, ACID, time travel, schema evolution) for migrated data.
• Integrate Databricks with AWS/S3 or Azure ADLS, ADF/Synapse, Key Vault, and Snowflake as required.
• Optimize Databricks clusters, jobs, and queries for performance and cost.
• Implement incremental loads, CDC patterns, and batch schedules for large datasets.
• Collaborate with Snowflake and dbt teams to ensure consistent data models and data contracts.
• Participate in data validation and reconciliation between DB2 400 / Guiderwire and Databricks outputs.
• Follow coding standards, version control, and CI/CD practices using Git/Azure DevOps.
• Provide defect fixes and support during SIT/UAT and post go-live stabilization.
Experience :
Legacy Demystification & Ingestion (DB2/400 & Guidewire) Looking to get Placed? Try our Placement Guarantee Plan
8+ years of experience in databricks with understanding complex legacy data models and getting that data into the cloud:
• Extracting DB2/AS400: Experience with Change Data Capture (CDC) or scheduled batch extractions from DB2 into cloud storage. Involves working through JDBC connections, mapping table dependencies, and re-platforming legacy SQL to distributed computing standards.
• Handling Guidewire Data: Integrating with Guidewire Cloud Data Access (CDA) or InsuranceSuite to replicate complex P&C (Property & Casualty) insurance schemas. Senior engineers parse these highly normalized operational databases and transform them into analytical-friendly schemas in the cloud.
2. Architecture & Pipeline Development
The core of the experience involves transitioning these legacy, row-based stores into a scalable Medallion Architecture (Bronze, Silver, Gold layers):
• Business Logic Refactoring: Translating rigid legacy procedural code (e.g., RPG/COBOL background logic, stored procedures) into scalable distributed patterns (PySpark, Spark SQL, and Scala).
3. Data Governance & Observability
A senior engineer is expected to govern vast amounts of incoming and generated data across the enterprise:
• Unity Catalog: Implementing strict data governance, lineage tracing, and table-level security.
• Data Quality: Automating data validation frameworks to ensure a seamless transition from legacy to modern systems without data loss or corruption.
4. Integration with the Databricks Platform Ecosystem
Moving beyond basic storage to utilizing the full power of the Databricks Data Intelligence Platform:
• Serverless Compute: Managing Databricks serverless resources, ensuring optimal cluster sizing, and reducing compute costs.
• Streaming and Batch Workflows: Building event-driven pipelines using features like Databricks Auto Loader to ingest flat files and streaming records directly into Delta tables.
Skills
CGoScalaSQLApache SparkPySparkDbtSnowflakeDatabricksETLAWSAzureCI/CDApacheServerlessIf a job posting appears fraudulent, asks for payment, contains misleading information, or violates our guidelines, please report it immediately. Our team will review it promptly, Jobaaj does not charge any fee from the applicants.
About Company
NTT DATA is a global IT services provider, headquartered in Tokyo, Japan, that delivers a broad range of innovative technology solutions across various sectors. As part of the NTT Group, one of the largest telecommunications companies in the world, NTT DATA specializes in consulting, IT and network services, and system integration. NTT DATA careers offer a vibrant landscape for professionals eager to develop cutting-edge technology solutions that drive significant transformations in business and society. Those pursuing NTT DATA careers can expect to engage in projects that blend global insights with local expertise, fostering a culture of innovation and a commitment to client success.
Important dates & deadlines?
Application Deadline
01 Dec 26, 01:55 PM IST
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Data Engineer Sr (Databricks)
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