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Job Description

Role Title: Senior Data Architect

Location: London, UK

Work Model: Hybrid (2 days/week onsite)

Contract Duration: 6–12 Months

Role Overview

We are seeking a hands-on Senior Data Architect to lead the design and delivery of scalable, event-driven data platforms for high-volume transactional systems, with a strong focus on payments and financial data.

You will define end-to-end As-Is to To-Be data architecture, build resilient streaming pipelines, and architect AWS- lakehouse platforms capable of handling tens of millions of events per day. This role requires close collaboration with engineering, platform, and business stakeholders to deliver secure, observable, and high-performance data products.

Key Responsibilities

Data Architecture & Products

Design and deliver high-performance data products including: Channel Operations Warehouse (short-term, low-latency layer) Channel Analytics Data Lake (long-term historical layer) Define and expose status and statement APIs with clear SLAs. Architect AWS lakehouse solutions using S3, Glue, Athena, Iceberg, and Redshift. Enable analytics and dashboards using Amazon QuickSight.

Streaming & Event-Driven Design

Build event-driven pipelines using Kafka (Confluent/MSK), Kinesis, Kinesis Firehose. Implement CDC, connectors, partitioning, replay, retention, and idempotency patterns. Define event contracts using Avro/Protobuf with Schema Registry, compatibility rules, and versioning. Use Amazon EventBridge for AWS- event routing and filtering.

Migration & Transformation

Assess APIs, file feeds, SWIFT messages, Aurora PostgreSQL, and Kafka topics. Define migration waves, cutover strategies, and runbooks.

Governance, Security & Quality

Apply data mesh and data-as-a-product principles. Define data ownership, access controls, lineage, and retention. Implement security using IAM, KMS encryption, tokenization, and audit trails.

Observability & Performance

Build monitoring using Grafana, Prometheus, CloudWatch. Track KPIs such as throughput, lag, success rate, and cost efficiency.

Hands-on Engineering

Develop/review code in Python, Scala, SQL. Build pipelines using Spark, AWS Glue, Lambda, Step Functions. Implement Terraform and CI/CD using GitLab/Jenkins.

Must-Have Skills & Experience

Total experience: 12+ years in data/engineering roles Relevant as Architect: 5+ years as Data / Solution / Streaming Architect Strong expertise in Kafka (Confluent/MSK) and AWS Kinesis Hands-on experience with Schema Registry, schema evolution & governance Proven experience in ISO 20022 payments messaging (PAIN, PACS, CAMT, SWIFT MX) Strong background in AWS Lakehouse using S3, Glue, Athena, Iceberg, Redshift Experience using Amazon EventBridge for event routing/orchestration Solid understanding of data modeling, CQRS, event sourcing & DDD Strong AWS experience: Lambda, Step Functions, IAM, KMS Excellent communication and stakeholder management skills

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