GCP Data Lead
ascendion
Job Description
- Assess and analyze Oracle schemas, PL/SQL programs, Informatica mappings/workflows, Pro*C programs, SQL scripts, schedules, dependencies, data volumes, interfaces, and data lineage to define migration and modernization strategies.
- Define scalable and secure GCP target architectures leveraging BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer, Pub/Sub, Datastream, Cloud SQL, AlloyDB, and other relevant GCP services.
- Analyze and map Oracle data types, partitioning, indexing, constraints, sequences, stored procedures, packages, triggers, and embedded business logic to GCP-native solutions, identifying opportunities for refactoring and modernization.
- Lead the modernization of Informatica PowerCenter mappings, sessions, and workflows into GCP-native patterns using SQL, Dataflow/Apache Beam, Dataproc/Spark, and Cloud Composer.
- Design and implement bulk and incremental data migration, CDC, orchestration, restartability, idempotency, error handling, auditability, lineage, observability, security, and cost/performance optimization.
- Assess and modernize Pro*C and embedded SQL workloads, including host variables, cursors, transaction handling, file processing, and batch processing patterns.
- Establish robust data reconciliation and traceability frameworks covering record counts, control totals, balances, transformations, data integrity, and critical business rules.
- Lead migration testing, data validation, performance testing, cutover planning, rollback strategy, production readiness, and hypercare.
- Define and enforce data engineering standards, coding practices, architecture patterns, security controls, and CI/CD practices across the migration program.
- Evaluate and incorporate Agentic AI capabilities and industry-standard agentic implementation platforms where they can accelerate migration, modernization, testing, documentation, or operational processes.
- Communicate architecture decisions, technical risks, dependencies, assumptions, and delivery readiness to client stakeholders, architects, and distributed engineering teams.
- Provide hands-on technical guidance and troubleshoot complex migration and production issues across the data platform.