Lead, mentor, and grow a team of data engineers, building a culture of ownership, craft, and continuous improvement
Own hiring, onboarding, and performance management for the data engineering function
Act as a technical role model — setting high standards while remaining approachable and supportive
Own the architecture, reliability, and evolution of our GCP data platform — including BigQuery, Cloud Composer/Airflow, Dataflow, Pub/Sub, and GCS
Design and maintain robust, scalable pipelines for ingesting, transforming, and serving diverse alternative datasets (web, CPG, transaction data, etc.)
Drive infrastructure best practices: cost optimisation, observability, incident response, and disaster recovery
Ensure data security, access controls, and compliance standards appropriate for regulated financial services clients
Translate business priorities and client requirements into a clear, deliverable technical roadmap
Partner with data operations, data science, and product teams to accelerate dataset onboarding and expand platform capabilities
Represent data engineering at the leadership level — contributing to company strategy and advocating for data quality as a core business value

Requirements

10+ years in data engineering, with at least 3 years in a leadership or management role (managing managers and teams)
Proven experience building and operating large-scale data pipelines on Google Cloud Platform
Experience in fintech, alternative data, financial data, or another data-as-a-product environment strongly preferred
Track record of delivering high-quality data infrastructure in a fast-moving, commercially sensitive context
Deep expertise across the GCP data stack: BigQuery, Dataflow, Pub/Sub, GCS, Cloud Composer, and related services
Hands-on experience with dbt (Core or Cloud) for scalable transformation layer design, including modeling patterns, testing frameworks, and documentation standards
Strong understanding of data pipeline design, ELT/ETL patterns, data modelling, and workflow orchestration
Solid grasp of data governance, quality frameworks, and security best practices
Familiarity with the unique challenges of alternative data — diverse formats, inconsistent schemas, high ingestion volumes, and strict data provenance requirements
Practical experience with infrastructure-as-code tooling (Terraform and/or Pulumi) for provisioning and managing cloud resources; able to set IaC standards and review infrastructure changes with the same rigour applied to application code
Strong proficiency in Python and SQL; comfortable reviewing code and setting engineering standards across the team.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringdata pipeline designELTETLdata modelingworkflow orchestrationPythonSQLdbtinfrastructure-as-code

Soft Skills

leadershipmentoringcommunicationcollaborationproblem-solvingtechnical role modelingperformance managementstrategic thinkingadaptabilityownership