Role: Data Architect -Mainframe Migration & Modernization
Location: 250 Bishopsgate, London, UK (Hybrid- 2 days in a week)
Rolling Extendable Contract (Inside IR35)

The Role
As a - Mainframe Data Architect with data migration expertise, you will be responsible for moving critical data off the Mainframe with zero surprises. Your responsibilities include designing robust Change Data Capture (CDC) strategies, ensuring accurate data landing and transformation, creating optimized data models, and executing a seamless cutover process.

Your responsibilities:
Design and implement CDC pipelines using IBM CDC tools or equivalents, including subscription management, bookmarks, and replay strategies.
Handle complex data encoding transformations, such as EBCDIC to UTF-8 and packed decimal conversions, with validation test suites.
Utilize migration tooling for schema conversion and downstream analytics (Glue, Athena, Redshift), with infrastructure-as-code (Terraform) and CI/CD (GitLab).
Plan and execute cutovers with dual-run validation, reconciliation, rollback strategies, and data governance controls (masking, encryption, IAM).
Develop observability dashboards for lag, throughput, error rates, and cost using CloudWatch/Grafana, with operational runbooks and alerting.
Ensure data quality through pre-migration validation tests and reconciliation against golden sources.
Apply domain-driven design principles to model bounded contexts and aggregate roots.
Architect event-driven systems using CDC as event streams, with replay and orchestration patterns
Translate Db2 schemas to target pipelines(Aurora Postgress preferred), including logical and physical data modelling, referential integrity, and denormalization decisions.
Build integration pipelines from Db2 to target pipelines (Aurora Postgress preferred) via Kafka/S3, ensuring idempotency, ordering, and reliable delivery semantics.

Your Profile
Change Data Capture: CDC design and operations (IBM, Precisely, or equivalent); subscription management, bookmarks, replay, backfill.
Db2 & z/OS knowledge: Db2 catalog, z/OS fundamentals, batch windows, performance considerations.
Relational modelling: Data modelling; normalization, indexing, partitioning; OLTP vs. analytics trade-offs.
Integration patterns: Kafka/hands-on, CDC-to-target pipelines, UPSERT/MERGE logic; Python/SQL; strong troubleshooting.
Data quality mindset: Write validation tests before migration; golden-source reconciliation.
Logical data modelling: Entity-relationship diagrams, normalization (1NF through Boyce-Codd/BCNF), denormalization trade-offs; identify functional dependencies and anomalies.
Physical data modelling: Table design, partitioning strategies, indexes; SCD types; dimensional vs. transactional schemas; storage patterns for OLTP vs. analytics.
Normalization & design: Normalize to 3NF/BCNF for transactional systems; understand when to denormalize for queries; trade-offs between 3NF, Data Vault, and star schemas.
Domain-Driven Design: Bounded contexts and subdomains; aggregates and aggregate roots; entities vs. value objects; repository patterns; ubiquitous language.
Event-driven architecture: Domain events and contracts; CDC as event streams; idempotency and replay patterns; mapping Db2 transactions to event-driven architectures; saga orchestration.
CQRS patterns: Command/query separation; event sourcing and state reconstruction; eventual consistency, when CQRS is justified for Mainframe migration vs. overkill.
Database internals: Index structures (B-tree, bitmap, etc.), query planning, partitioning strategies; how Db2 vs. PostgreSQL differ in storage and execution.
Data quality & validation: Designing test suites for schema conformance; referential integrity checks; sampling and reconciliation strategies.

Desirable skills/knowledge/experience:
IBM zDIH patterns, zIIP tuning.
Cobol copybook/VSAM ingestion experience.
Postgress SQL Data Architecture, PostgreSQL/Aurora data modelling