Data Engineer

Serve as the hands-on engineering lead driving technical discovery, migration execution, and modernization of the client's legacy Oracle data platform into a scalable, AI-ready Postgres ecosystem.
This role focuses on building robust data pipelines, migration frameworks, and validation mechanisms to enable analytics, predictive CX, and future AI/ML workloads.
Technical Discovery & Assessment
• Perform deep analysis of:
o Oracle schemas, stored procedures, and data models
o Existing ETL/ELT pipelines, batch jobs, and performance bottlenecks
• Identify migration complexity, technical debt, and optimization opportunities
Data Mapping & Migration Design
• Define source-to-target mappings from Oracle Postgres
• Document:
o Data transformations
o Business rules
o Lineage and dependencies
• Establish migration approaches including:
o Schema conversion
o Data replication and validation strategies
Build scalable pipelines for:
• Ingestion
• Transformation
• Replication and synchronization
Enable transition from batch-driven systems real-time/event-driven architecture
Schema Modernization & AI Readiness
• Redesign schemas to support:
o AI/ML workloads
o Real-time analytics
o High-frequency ingestion
• Enable AI-extensible and vector-ready data structures (e.g., embeddings support, pgvector or similar patterns)
• Support separation of operational vs analytical workloads
Pipeline Development & Validation
• Build and validate:
o Data ingestion and transformation pipelines
o Data quality and reconciliation frameworks
• Develop proof-of-concepts for:
o Near real-time processing
o Scalable pipeline patterns
• Ensure data accuracy, completeness, and consistency post-migration

Performance Optimization
• Recommend and implement:
o Partitioning and clustering strategies
o Indexing and query optimization
• Tune Postgres workloads for:
o High concurrency
o Large-scale analytical queries
o Mixed OLTP + analytical use cases

Observability, Data Quality & Governance
• Design and implement:
o Monitoring, logging, and alerting frameworks
o Data quality checks and SLA monitoring
• Integrate observability into pipelines to ensure reliability and traceability
• Align with:
o Data governance policies
o Security and compliance standards

Delivery & Collaboration
• Collaborate with:
o Data architects on target-state design
o Business analysts on requirements and validation
• Support modernization sequencing by identifying:
o Risks
o Dependencies
o Implementation constraints
• Produce:
o Implementation-ready designs
o Technical documentation
o Migration playbooks

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Required Skills & Experience
• 6-10+ years of experience in Data Engineering or Platform Engineering
• Strong hands-on expertise in:
o Relational databases (Oracle, Postgres)
o Data migration and re-platforming initiatives
o Data pipeline development (ETL/ELT frameworks)
• Experience with:
o CDC and streaming technologies (Kafka, Debezium, etc.)
o Data modeling and schema optimization
o Performance tuning in Postgres or similar systems
• Proven ability to:
o Build scalable, production-grade data pipelines
o Validate data integrity across large-scale migrations
o Develop PoCs and translate them into production solutions


Nice to Have Skills & Experience
• Experience in large-scale Oracle Postgres migrations
• Exposure to:
o Cloud-native data platforms (GCP, AWS, or Azure)
o Streaming/event-driven architectures
• Familiarity with:
o Vector databases / embeddings frameworks
o AI/ML data pipelines and feature engineering
• Experience with:
o Infrastructure-as-Code (Terraform or similar)
o CI/CD for data pipelines


Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.