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Data Architect – Mainframe Migration & Modernization

Avance Consulting
Greater London
2 days ago
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The Role

As a – Mainframe Data Architect, you will be responsible for moving critical data off the mainframe with zero surprises. Design CDC, land it right, model it right, cut over cleanly.

Your responsibilities:

• Design and implement CDC pipelines using IBM CDC tools or equivalents, including subscription management, bookmarks, and replay strategies.

• Translate Db2 schemas to Aurora PostgreSQL, including logical and physical data modelling, referential integrity, and denormalization decisions.

• Build integration pipelines from Db2 to Aurora via Kafka/S3, ensuring idempotency, ordering, and reliable delivery semantics.

• 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

Your Profile

Essential skills/knowledge/experience:

• 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: PostgreSQL/Aurora 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.

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