workable

Lead Data Engineer

CV-Library

GBR

Full-time

Senior

Hybrid

Discovered 2 weeks ago

AWSSQLdbtPythonAmazon RedshiftApache Airflow

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Responsibilities

Define and drive the technical strategy for our AWS-based data platform and Data Engineering function.
Lead the design and delivery of scalable, reliable and cost-effective data solutions.
Build and optimise modern batch and real-time data pipelines to support business growth.
Own and evolve our data architecture, ensuring scalability, performance and maintainability.
Champion engineering best practices, including code reviews, technical standards and architectural governance.
Develop robust data models and datasets that power reporting, analytics, product insights and machine learning.
Drive improvements in data quality, observability, monitoring and platform reliability.
Lead the adoption of Infrastructure as Code, CI/CD and automation across the data platform.
Work closely with analysts, data scientists and business stakeholders to turn data requirements into impactful solutions.
Evaluate and implement new technologies, including AWS AI services, to enhance platform capabilities.
Lead incident resolution, root cause analysis and continuous improvement initiatives.
Mentor and develop a team of Data Engineers, fostering a culture of technical excellence, ownership and collaboration.
Requirements
Strong commercial experience in Data Engineering , with experience leading or mentoring engineers.
Strong experience designing and building cloud-based data platforms , ideally on AWS.
Excellent SQL skills and strong experience with analytical data modelling.
Strong hands-on experience with dbt in a production environment.
Experience building and operating production-grade data pipelines.
Strong Python development skills.
Experience with data warehouses such as Amazon Redshift .
Experience with orchestration technologies such as Apache Airflow .
Experience with infrastructure as code, ideally Terraform .
Good understanding of CI/CD and modern software engineering practices.
Experience working with both batch and event-driven/streaming data.
Strong understanding of data quality, monitoring, observability and operational reliability.
Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
A pragmatic approach to engineering: knowing when to build, when to improve and when to keep things simple.
We are actively committed to promoting a fully diverse and inclusive workforce and we welcome applications for this role from all candidates who meet the key requirements. Please do not hesitate to get in touch should you require any reasonable adjustments to assist with your application.

Requirements

Strong commercial experience in Data Engineering , with experience leading or mentoring engineers.
Strong experience designing and building cloud-based data platforms , ideally on AWS.
Excellent SQL skills and strong experience with analytical data modelling.
Strong hands-on experience with dbt in a production environment.
Experience building and operating production-grade data pipelines.
Strong Python development skills.
Experience with data warehouses such as Amazon Redshift .
Experience with orchestration technologies such as Apache Airflow .
Experience with infrastructure as code, ideally Terraform .
Good understanding of CI/CD and modern software engineering practices.
Experience working with both batch and event-driven/streaming data.
Strong understanding of data quality, monitoring, observability and operational reliability.
Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
A pragmatic approach to engineering: knowing when to build, when to improve and when to keep things simple.

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