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We are looking for a Data Tech Lead to join our Data Engineering practice, delivering modern data platforms for enterprise and regulated clients. This is a hands‑on leadership role for a technically strong engineer who can lead design and delivery, act as a trusted technical authority, and mentor engineers while maintaining strong engineering discipline in real‑world environments.
This is a delivery‑focused role for an experienced engineer and Tech Lead who enjoys solving complex data challenges, takes ownership of outcomes, and applies strong engineering discipline in real‑world environments.
Leading end‑to‑end delivery of data engineering workstreams; shaping solution approach, setting technical direction, and ensuring outcomes are delivered to a high standard
Designing and building scalable batch and streaming pipelines and operating production systems
Providing technical governance and oversight: design reviews, implementation guidance, risk/issue escalation, and delivery assurance
Building strong stakeholder relationships and operating as a credible client‑facing technical lead
Coaching and mentoring engineers, supporting learning plans, and helping develop capability standards and accelerators
Partnering with business and technology stakeholders to build and enhance reliable, scalable data platforms
Developing high‑throughput, low‑latency data processing systems
Working within the Databricks and Apache Spark ecosystem to support large‑scale data workloads
Building and maintaining cloud‑native data solutions on AWS
Using dbt for data transformation, modelling, testing, and documentation
Orchestrating data workflows using Airflow or similar orchestration tools
Writing clean, efficient, and well‑tested code following software engineering best practices
Collaborating closely with product, analytics, and platform teams
Supporting production systems by troubleshooting issues and implementing continuous improvements
Ensuring solutions are production‑ready: secure, tested, observable, and cost‑efficient
Optimising data performance, reliability, and data quality in live environments
