Db Senior Engineer

Section

Details

Job Title

DB2 Senior Engineer

Job Type

Full Time

Client Location

Remote

Work Arrangement

Remote

Duration

Full Time

Pay Rate / Salary

$100-$130k/yr.

Job Summary

• Design and develop scalable data-engineering solutions supporting the migration of IBM DB2 data and workloads to the Databricks Lakehouse.
• Analyze DB2 database objects and dependencies, modernize SQL and legacy ETL workflows, validate migrated data, and optimize high-volume Databricks workloads.
• Collaborate with business, data engineering, cloud, and architecture teams on enterprise data-modernization initiatives.

Key Responsibilities

• Analyze and extract data from IBM DB2 databases for migration to the Databricks Lakehouse.
• Design and develop scalable ETL and ELT pipelines connecting DB2 and Databricks.
• Extract inventories of DB2 schemas, tables, views, aliases, stored procedures, functions, triggers, and sequences.
• Perform database-object and dependency validations.
• Convert DB2 SQL, stored procedures, and legacy ETL workflows into scalable Databricks solutions.
• Translate DB2 security grants and sensitive-data access controls into corresponding controls using Databricks Unity Catalog.
• Apply knowledge of DB2 structures and data models supporting property and casualty insurance products.
• Validate data quality, reconciliation, completeness, and migration accuracy between source and target platforms.
• Optimize high-volume data ingestion, transformations, Spark jobs, and Databricks workloads.
• Collaborate with business, data engineering, cloud, and architecture teams supporting data-modernization programs.
• Use Databricks AI and machine-learning capabilities to support AI-enabled data-engineering and migration solutions.
• Use generative AI or AI coding assistants to accelerate code analysis, conversion, documentation, and modernization.
• Apply large language models and prompt engineering to SQL transformation, code explanation, dependency analysis, and migration-artifact generation.
• Build or use AI-assisted data-quality and reconciliation frameworks to identify anomalies, schema mismatches, transformation discrepancies, and migration defects.
• Apply retrieval-augmented generation patterns to database metadata, data dictionaries, mapping documents, and migration knowledge bases.
• Develop Python- or PySpark-based automation utilities for metadata discovery, schema mapping, code conversion, test-case generation, and migration validation. Integrate AI-assisted development into CI/CD and data-engineering workflows.

Required Qualifications

• IBM DB2 and AS400
• Databricks
• DB2-to-Databricks data migration
• ETL and ELT pipeline development
• DB2 schemas, tables, views, aliases, stored procedures, functions, triggers, and sequences
• DB2 Catalog SQL
• DB2 LUW command-line and SQL clients, including DBeaver and Data Studio
• Mainframe TSO/ISPF
• Lakebridge Analyzer
• Databricks Unity Catalog
• SQL and stored-procedure modernization
• Data-quality validation and reconciliation
• Python and PySpark

• Property and casualty insurance domain knowledge AI and generative AI capabilities for data engineering and migration, as an added advantage