IT & Software

Data Engineer

Matchtech

Surrey · Surrey · United Kingdom

Overview

In this role, you design, build and operate scalable data pipelines and models that convert diverse sources into analytics-ready datasets for ML and analysis. You’ll support batch, streaming and interactive workflows across Azure, edge and on-prem environments, collaborating with data scientists, analysts and engineers in an agile setting. You will develop reusable platform components and ensure data quality, reliability and performance. This position offers hands-on impact shaping data products for mission-critical applications and advanced analytics.

Pay / Benefits
  • Bonus scheme
  • Private healthcare + cash plan
  • Life assurance (4x salary)
  • Share options
  • Pension
  • Flexibility (Hybrid working)
Responsibilities
  • Build and maintain batch and streaming data pipelines (ingestion, transformation, orchestration)
  • Monitor production data services and resolve data quality and performance issues
  • Develop reusable platform components and tooling to boost engineering productivity
  • Implement automated tests, validation checks and integration plans for data pipelines
  • Design data models and storage patterns to support analytics, ML features, embeddings and conversational querying
  • Document data flows, schemas and technical decisions
Key requirements
  • Strong Python for production-grade data engineering code
  • Strong SQL and data modeling experience
  • Experience with structured/time-series/high-volume storage (SQL databases, InfluxDB or similar)
  • Experience building batch and event-driven/streaming pipelines
  • ~3+ years in a data engineering/data platform team
  • Familiarity with distributed processing (Spark, Flink, or similar)
  • Orchestration tooling to schedule/monitor/recover pipelines
  • Understanding of event-driven architecture, message brokers and stream-processing patterns
  • Hands-on with Azure data services and cloud data platform patterns
  • Docker antibodies; comfortable building/debugging Docker containers
  • Experience deploying/operating data workloads on Kubernetes (cloud/edge/on-prem)
  • Experience developing/consuming APIs for ingestion, access and integration
  • Strong attention to detail; able to prioritise independently; solid communicator
  • Strong communication
  • Independent prioritisation
  • Collaboration in cross-functional teams
  • Python
  • SQL
  • SQL databases

Reference: WJ-747_31055840

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