• Design, build and maintain data pipelines, ETL processes and data models
• Make and document architectural and data-modelling decisions
• Integrate and transform diverse data sources into a reliable, unified data platform
• Design and implement database schemas for large volumes of structured and unstructured data
• Build scalable and maintainable data solutions supporting analytics, reporting, operational processes and data-driven products
• Champion engineering standards across SQL, Python, testing, documentation and code review
• Review designs and code produced by other engineers
• Identify and address technical debt and improve the data platform
• Optimise data solutions using partitioning, indexing and caching
• Develop and maintain data quality processes
• Improve reliability, observability and performance of data solutions
• Collaborate with product managers, developers, data colleagues and business stakeholders to define requirements
• Diagnose and resolve performance and production issues
• Coach and mentor engineers
• Keep up to date with data engineering developments and evaluate new technologies
• Participate in the team’s out-of-hours support rota where required

Requirements

• Strong commercial data engineering experience, ideally in a senior or lead capacity
• Significant experience delivering production data engineering solutions
• Advanced SQL and an excellent understanding of databases
• Strong Python skills for data engineering
• Strong understanding of data warehousing and dimensional/data modelling
• Experience designing and operating production data pipelines
• Experience with a modern cloud data warehouse such as Snowflake, BigQuery or Redshift
• Experience with automated testing, version control and CI/CD
• Strong understanding of data quality, reliability and observability
• Experience diagnosing performance and production issues
• Ability to make, document and communicate technical design decisions
• Experience mentoring or supporting other engineers
• Excellent written and verbal communication skills
• Desirable: Experience with Snowflake, dbt or Fivetran
• Desirable: Experience working with AWS / Glue
• Desirable: Experience with MySQL or SQL Server
• Desirable: Experience with Salesforce
• Desirable: Familiarity with JSON and data integration formats

Core Competencies

Demonstrates expertise in designing and maintaining data pipelines, ETL processes, and data models, with a strong focus on SQL and Python for data engineering. Proven ability to optimize data solutions for performance and reliability while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

• Data Engineering Experience
• Advanced SQL Skills
• Strong Python Skills
• Cloud Data Warehouse Experience
• Data Quality and Reliability

Hard Skills

• Data Pipeline Design
• ETL Processes
• Data Modelling
• Database Schema Design
• Automated Testing
• Version Control
• CI/CD
• Performance Diagnosis
• Data Quality Processes
• Technical Documentation

Soft Skills

• Excellent Communication Skills
• Mentoring and Coaching

Industry Keywords

• Data Warehousing
• Dimensional Modelling
• Data Integration
• Observability
• Technical Debt

Tools & Technologies

• Snowflake
• BigQuery
• Redshift
• AWS
• Glue
• MySQL
• SQL Server
• Dbt
• Fivetran
• JSON