Job-Specific Essential Duties and Responsibilities:
Data Architecture & Migration Strategy
- Own the end-to-end technical architecture for complex data migration initiatives from legacy systems to modern data platforms.
- Define target-state data architectures including modern applications, data lakes, warehouses, lakehouse patterns, and real-time/streaming integrations.
- Design migration strategies (phased, domain-based, parallel run, cutover) based on data criticality, volume, and business risk.
- Ensure alignment with enterprise data architecture, integration standards, and cloud platform strategies.
Data Engineering & Technical Delivery
- Lead hands-on technical design and delivery of data ingestion, transformation, and persistence layers.
- Establish standards for ETL/ELT pipelines, orchestration, schema management, metadata, and error handling.
- Coordinate implementation across matrixed data engineers, application teams, platform engineers, QE, and operations.
- Ensure pipelines meet non-functional requirements for performance, scalability, resiliency, availability, and cost efficiency.
Data Quality, Validation & Governance
- Architect and govern data validation, reconciliation, and control frameworks for all migrations.
- Ensure data completeness, accuracy, consistency, and referential integrity across source and target systems.
- Implement data lineage, auditability, and traceability to support regulatory, financial, and operational needs.
- Partner with Security, Privacy, and Compliance teams to enforce data protection, encryption, masking, and access controls.
Program Execution & Delivery Accountability
- Manage technically complex, multi-stream data programs spanning multiple source systems and consumer platforms.
- Build and maintain detailed technical migration roadmaps, dependency maps, and milestone plans.
- Identify and mitigate risks related to data integrity, performance bottlenecks, schema drift, and operational readiness.
- Lead cutover execution, rollback planning, and post-migration stabilization.
Testing, Readiness & Production Operations
- Define and enforce test strategies for data migrations, including unit testing, data reconciliation testing, performance testing, and business validation.
- Partner with QE and UAT teams to ensure business data correctness and outcome validation.
- Own technical production readiness reviews and go-live criteria.
- Ensure operational monitoring, alerting, and incident response mechanisms are implemented prior to go-live.
Platform Enablement & Modern Data Capabilities
- Partner with Cloud and Platform teams to optimize infrastructure performance, reliability, and cost.
- Enable consumption-ready data models for analytics, reporting, APIs, and AI/ML workloads.
- Drive adoption of automation, Infrastructure-as-Code, and CI/CD for data pipelines.
Stakeholder & Cross-Functional Leadership
- Serve as the primary technical authority for data migration and data platform delivery.
- Communicate complex technical risks, tradeoffs, and architecture decisions in business-relevant terms.
- Coordinate closely with Business, Product, Architecture, Analytics, PMO, and Operations leaders.
Team Leadership & Engineering Excellence
- Lead and mentor data engineering managers, senior engineers, and technical leads.
- Establish engineering standards, design review practices, and technical governance.
- Build a culture of engineering rigor, automation, quality, and continuous improvement.
Success Measures:
- Successful delivery of complex data migrations with high data accuracy and integrity.
- Stable, scalable, and secure modern data platforms in production.
- Minimal post-migration defects and data issues.
- Improved trust in enterprise data for analytics and operations.
- High-performing data engineering teams delivering with technical rigor.