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Data Migration Engineer (Oracle/PostgreSQL → MongoDB)
Houston, TXMarch 26th, 2026
Job Title: Data Migration Engineer (Oracle/PostgreSQL → MongoDB) Location: Dallas, TX or Tampa, FL, USA Job Description We are seeking a highly skilled Data Migration Engineer to lead the migration of legacy Oracle Database and PostgreSQL databases from on-premises environments to cloud-based platforms. The target architecture will leverage MongoDB for semi-structured operational data and PostgreSQL for relational workloads, deployed on Amazon Web Services and Google Cloud Platform. This role will be responsible for designing and executing end-to-end data migration frameworks, including discovery, schema mapping, extraction, transformation, loading, validation, and production cutover. The ideal candidate will bring deep expertise in database modernization, ETL development, cloud migration strategies, and scalable data architecture. Key Responsibilities Migration Discovery and Planning Assess existing Oracle and PostgreSQL database environments, including schema complexity, data volume, dependencies, and application data access patterns. Define migration strategies such as phased migration waves, domain-based migration approaches, and rollback procedures. Identify data transformation requirements, compatibility gaps, and performance considerations. Target Data Architecture and Modeling Design a hybrid cloud data architecture using MongoDB for semi-structured and high-volume operational data (events, activity logs, nested objects). Use PostgreSQL for relational transactional workloads and structured reporting datasets. Develop data model mappings between relational schemas and MongoDB document structures, determining when to use embedding vs referencing. Custom Migration Tool Development Develop scalable migration tools using Python and Java to support ETL processes: Extract data from Oracle and PostgreSQL using batch processing and incremental extraction mechanisms. Transform data through schema normalization/denormalization, data type conversion, JSON document generation, and business rule transformations. Load data into MongoDB and PostgreSQL using optimized bulk operations and insert/update pipelines. Implement migration framework capabilities such as retry mechanisms, checkpointing, job resumability, and parallel processing for high-volume datasets. Data Validation and Reconciliation Implement automated validation frameworks to ensure data accuracy and integrity during migration. Perform validation checks including: Row and document count verification Checksum and hash validation Referential integrity checks Sampling-based record verification Generate reconciliation reports to support migration approval and stakeholder sign-off. Performance Optimization and Reliability Design migration pipelines that support parallel processing, data partitioning, and batch execution for large-scale datasets. Implement throttling and load-balancing mechanisms to minimize performance impact on source systems. Cutover and Post-Migration Stabilization Coordinate production cutover activities, including final data synchronization and validation checks. Support post-migration monitoring, troubleshooting, and performance tuning to stabilize the target environment. Technology Stack Cloud Platforms Amazon Web Services Google Cloud Platform Monitoring and Observability Datadog for monitoring migration pipelines, job health, system performance, and alerting. Programming Languages Python – orchestration scripts, transformation logic, automation, and validation frameworks. Java – high-performance migration services and scalable multi-threaded processing components. Required Qualifications 7+ years of experience in data engineering, database migration, or data platform modernization. Strong hands-on experience with Oracle, PostgreSQL, and MongoDB. Proficiency in Python and Java for building scalable ETL pipelines. Experience performing large-scale data migrations to cloud platforms. Experience working with AWS or GCP cloud environments. Strong knowledge of data modeling, ETL processes, and distributed data processing. Preferred Qualifications Experience migrating legacy relational databases to NoSQL systems. Experience implementing data validation frameworks and reconciliation processes. Familiarity with monitoring and observability tools such as Datadog. Knowledge of high-availability and fault-tolerant migration architectures.
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