Software Developer in Test working on cloud - based data platform at Tecsys. Ensuring quality and reliability of data pipelines and transformations using automation frameworks.
About the role
- Principal Data Engineer at Trainline shaping robust data foundations for AI and ML-driven products. Collaborate with cross-functional teams to ensure best practices in data engineering and ML.
Responsibilities
- Act as a technical authority across multiple teams, setting standards and patterns for data and ML‑adjacent infrastructure
- Embed with ML teams to design, build and evolve data platforms supporting AI and ML workloads
- Influence technical direction without direct line management responsibility
- Partner with Data Engineering teams outside of ML to build a community and share best practices and findings across all areas
- Identify systemic issues and proactively drive improvements across the data ecosystem
- Look for short term and strategic opportunities to enhance core platforms with new self-serve enablement features for ML and DE
- Partnering with MLEs to design data pipelines supporting model training, inference and experimentation
- Designing and reviewing architectures for ML‑ready data platforms
- Building and optimising data pipelines using SQL, Spark or Ray and Python
- Defining best practices for orchestration using Airflow or similar tools
- Supporting API‑driven and event‑based data access patterns
- Working with AWS infrastructure such as ECS, vector databases and Bedrock APIs
- Reviewing designs and code across teams to raise quality and consistency
- Coaching engineers through pairing, design reviews and informal mentoring
- Collaborating on innovative AI‑powered product features such as the Travel Assistant
Requirements
- Extensive experience as a Senior, Staff or Principal Data Engineer operating across teams
- Deep expertise in SQL and Python, with strong experience in Spark or similar tooling.
- Strong understanding of orchestration tools such as Apache Airflow
- Experience designing data platforms for ML and AI workloads
- A track record of introducing new technologies and practices, and handling ambiguity and multiple stakeholders.
- Hands‑on experience with AWS infrastructure (e.g. ECS, IAM, data storage, compute)
- Familiarity with vector databases and modern AI/ML APIs (e.g. Bedrock)
- Experience working closely with Machine Learning Engineers in production environments
- Strong system design skills and the ability to influence through technical leadership
Benefits
- Private healthcare & dental insurance
- Generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme to further reduce carbon emissions
- Extra festive time off
- Excellent family-friendly benefits
- Career growth with clear career paths
- Transparent pay bands
- Personal learning budgets
- Regular learning days
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