Director, Data Engineering
E
EverwayEdTech SaaS
Remote- UKFull-TimeDirector
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 3+ years in data engineering, with 2+ years in a leadership or senior technical role
- Required Skills
- AWSPythonSQLAirflowSparkdbtDatabricks
Requirements
- 3+ years in data engineering
- 2+ years in a leadership or senior technical role
- Experience operating in complex environments (e.g., M&A, multi-system landscapes, platform migrations)
- Strong hands-on experience with Databricks (Delta Lake, Unity Catalog, Spark)
- Proficiency in Python and SQL for building data pipelines
- Experience with dbt or equivalent transformation frameworks
- Experience building and maintaining scalable data pipelines (e.g., Fivetran, Airflow, or similar)
- Strong understanding of data modelling, warehousing concepts, and lakehouse architecture
- Proven ability to define and enforce engineering standards (testing, CI/CD, documentation, observability)
- Experience with cloud platforms (preferably AWS)
- Ability to balance hands-on technical work with team leadership and stakeholder collaboration
- Strong communication skills, with the ability to translate technical decisions into business impact
Responsibilities
- Lead, mentor, and develop a team of data engineers, fostering a culture of ownership, quality, and collaboration
- Contribute hands-on to the design and build of data pipelines, integrations, and platform components
- Own and evolve the Databricks-based data lakehouse (Delta Lake, Unity Catalog), including architecture, performance, and lifecycle management
- Define and enforce engineering standards across ingestion, transformation (dbt), naming conventions, access controls, and environment management
- Design scalable ingestion patterns (e.g., Fivetran) to support multiple source systems, including M&A-driven complexity
- Ensure reliable, well-documented ingestion with full history preservation and monitoring
- Partner with Data & Analytics on data contracts and modelling to ensure data is fit for downstream use cases
- Embed data quality, lineage, and governance into engineering workflows
- Drive engineering best practices across code quality, testing, CI/CD, documentation, and observability
- Own and optimise the transformation layer (dbt), including structure, testing, and performance
- Support operational excellence, including incident response and SLA adherence
- Partner with leadership on hiring, team growth, and capacity planning
View Full Description & ApplyYou'll be redirected to the employer's site
