Lead Data Engineer

OVERVIEW:

This role exists to provide technical leadership within the data engineering team setting the standard for engineering excellence while remaining deeply hands-on. The Lead Data Engineer drives the design and delivery of scalable resilient data platforms and pipelines that underpin Gymsharks ambition to be a truly data driven business. Sitting at the intersection of craft and collaboration this role shapes technical direction raises the capability of those around them and ensures the team builds the right things in the right way.

WHAT YOULL BE DOING:

Technical Leadership:

Own and drive the technical design and architecture of data pipelines data models and platform components across the team.
Set and enforce engineering standards: code quality testing observability security and documentation ensuring the whole team operates to them
Lead technical discovery design sessions and code reviews providing constructive actionable feedback that elevates team output.
Identify and drive resolution of technical debt proactively surfacing risks and proposing pragmatic solutions.
Evaluate emerging tools and technologies (within the GCP ecosystem and beyond) and make grounded recommendations to the Data Engineering Manager.
Work with the Data Engineering manager to find solutions to complex or ambiguous data engineering problems unblocking the team and stakeholders.
Ensure architectural decisions align with Gymsharks data strategy platform vision and evolving business needs.
Champion a culture of engineering excellence through example documentation and knowledge sharing.

Delivery:

Own and drive the technical design and architecture of data pipelines data models and platform components across the team.
Set and enforce engineering standards: code quality testing observability security and documentation ensuring the whole team operates to them.
Lead technical discovery design sessions and code reviews providing constructive actionable feedback that elevates team output.
Identify and drive resolution of technical debt proactively surfacing risks and proposing pragmatic solutions.
Evaluate emerging tools and technologies (within the GCP ecosystem and beyond) and make grounded recommendations to the Data Engineering Manager.
Work with the Data Engineering manager to find solutions to complex or ambiguous data engineering problems unblocking the team and stakeholders.
Ensure architectural decisions align with Gymsharks data strategy platform vision and evolving business needs.
Champion a culture of engineering excellence through example documentation and knowledge sharing.

People & Craft:

Mentor and coach Data Engineers (Junior through Senior) supporting their technical growth and career progression.
Facilitate knowledge sharing sessions pairing and documentation to build collective capability and reduce knowledge silos.
Contribute to hiring: lead technical interviews calibrate assessments and help onboard new team members effectively.
Partner with the Data Engineering Manager on team development planning identifying skill gaps and proposing learning opportunities.
Ensure team members feel supported challenged and set up to do their best work.

Governance & Collaboration:

Partner with Data Governance to embed data quality access control and privacy by design into all engineering work.
Collaborate cross functionally with Data Product and wider Tech teams to ensure joined up platform delivery.
Maintain accurate and comprehensive technical documentation: architecture decision records runbooks pipeline specs and data dictionaries.
Uphold data governance security and compliance standards across all data engineering activities.

WHAT YOULL NEED:

Essential Criteria:

Strong experience in data engineering in a senior or lead-level technical role.
Deep expertise in Google Cloud Platform:
Big Query Dataflow Pub/Sub Cloud Storage and Cloud Composer (Airflow) as the primary data platform stack.
Advanced Python and SQL skills including writing performant production grade code and conducting rigorous code reviews.
Proven experience designing and building complex scalable data pipelines using both batch and streaming/event driven patterns.
Strong data modelling skills: dimensional modelling data vault or equivalent with a track record of building well structured reusable Big Query data models.

Experience with Dataform (or equivalent SQL based transformation tools) for orchestrating transformations within Big Query at scale.
Solid understanding of software engineering principles: CI/CD version control (Git) testing frameworks and infrastructure as code (Terraform).
Demonstrated ability to embed data quality observability and alerting into pipelines (automated validation anomaly detection monitoring).
Experience leading technical design sessions owning architecture decisions and communicating trade offs clearly to both technical and non technical audiences.
Track record of mentoring or coaching engineers and growing technical capability within a team.
Strong cross functional…