29 days ago
Solihull, United KingdomStaff+
Responsibilities
- Own the technical design and architecture of scalable data pipelines, data models, and platform components.
- Set and enforce standards for code quality, testing, observability, security, documentation, and data governance.
- Lead technical discovery, design sessions, code reviews, architecture decisions, and technical debt resolution.
- Build and deliver batch and streaming/event-driven data pipelines and reusable BigQuery data models.
- Evaluate data engineering tools and technologies and make recommendations to the Data Engineering Manager.
- Mentor and coach Data Engineers from junior through senior levels and support their technical growth.
- Lead technical interviews, calibrate assessments, and help onboard new team members.
- Partner with Data Governance, Data Product, and wider Technology teams on platform delivery, data quality, access control, privacy, and compliance.
- Maintain architecture decision records, runbooks, pipeline specifications, and data dictionaries.
Requirements
- Strong experience in data engineering in a senior or lead-level technical role.
- Deep expertise with Google Cloud Platform, including BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer/Airflow.
- Advanced Python and SQL skills, including production-grade coding and code reviews.
- Experience designing and building complex scalable data pipelines using batch and streaming/event-driven patterns.
- Strong data modelling experience, including dimensional modelling, data vault, or equivalent approaches.
- Experience with Dataform or equivalent SQL-based transformation tooling for BigQuery.
- Understanding of software engineering principles, Git, testing frameworks, and Terraform.
- Experience embedding data quality, observability, alerting, automated validation, anomaly detection, and monitoring into pipelines.
- Experience leading technical design sessions, owning architecture decisions, and communicating trade-offs to technical and non-technical audiences.
- Track record of mentoring or coaching engineers and developing team capability.
- Strong cross-functional collaboration and stakeholder management skills.
- Preferred experience with DataProc/Spark, Looker, analytics engineering practices, data mesh or data platform architecture, GCP cost management, BigQuery cost optimisation, and ML infrastructure or feature engineering pipelines.
- Experience in e-commerce or retail data environments is desirable.
Benefits
- Performance-based bonus opportunity.
- Funded healthcare benefit, contributory employer pension scheme, life assurance, and enhanced family leave.
- 25 days of holiday, an additional birthday day, and Bank Holidays.
- Flexible benefits including salary sacrifice EV, dental insurance, cycle-to-work, technology, and holiday-trading schemes.
- Gymshark employee discount, long-service awards, high-street cashback and discounts, and financial, physical, and mental wellbeing support.
- Gym membership at The Lifting Club, onsite lunch provision, coffee bars, and EV charging points at the IQ office.
- Hybrid work arrangement requiring attendance at GSIQ, Solihull at least three days per week.
Tech Stack
Categories
Data Engineering
