Data Architect

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-native 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-native 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