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Stackstudio Digital Ltd. jobs

Data Architect - Mainframe Migration & Modernization

£110,000 - 121,000
Stackstudio Digital Ltd.
Trafalgar Square, South East London
£110,000 - 121,000
Company Size icon
Company Size
<50
Company Type icon
Company Type
Services
Exp Level icon
Exp Level
Regular
Job Type icon
Job Type
Full-Time
Language icon
Language
English
Visa sponsorship icon
Visa sponsorship
No

Requirements

Must:
- 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: IBM zDIH patterns, zIIP tuning; COBOL copybook / VSAM ingestion experience; Postgress SQL Data Architecture, PostgreSQL / Aurora data modelling.

Technologies

Redshift
CI/CD
CloudWatch
CQRS
Data Vault
GitLab

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.

Description


We are seeking a skilled Mainframe Data Architect specializing in migration and modernization. This role is based in our London office at 250 Bishopsgate, with a hybrid working model requiring office attendance two days a week. We focus on moving critical data off the mainframe with precision and minimal disruption. Our team values innovation, collaboration, and a strong commitment to data quality. Come join us to drive impactful change in a transformative environment.
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