Lead Data Engineer
Venesky-Brown’s client, a public sector organisation in Cardiff, is currently looking to recruit a Lead Data Engineer for an initial 12 week contract with potential to extend on a rate of £212.63/day (Inside IR35). This role will be working from home until further notice.
Responsibilities:
– Lead the design and implementation of scalable, reliable data pipelines and data platforms in the Google Cloud Platform.
– Collaborate with data scientists, analysts, and other engineering teams to define data requirements and optimize data workflows.
– Oversee the deployment and integration of data systems on the Google Cloud Platform.
– Ensure the security, compliance, and performance of Google Cloud Platform data solutions.
– Drive best practices in cloud-based data engineering, automation, and DevOps for data solutions.
– Mentor and guide Senior Data Engineers, contributing to team skill growth and knowledge sharing.
Essential Skills:
– Master’s Degree in Computer Science, Engineering, Information Technology, or related field.
– Cloud Platform Certification (AWS, Azure, or Google Cloud Platform)
– AWS Certified Data Analytics – Specialty
– Google Professional Data Engineer
– Microsoft Certified: Azure Data Engineer
– Experience in cloud platform as a service (PaaS).
– Ability to communicate between technical and non-technical stakeholders, managing expectations and supporting difficult discussions.
– Ability to support teams to apply a range of techniques for data profiling, undertake source system analysis and bring multiple data sources together.
– Can establish enterprise-scale data integration procedures across the data development life cycle.
– Ability to manage resources to ensure that data services work effectively.
– Can identify areas of innovation in data tools and techniques.
– Ability to establish and maintain standards, remaining informed of industry best practice.
– Can understand concepts and principles of data modelling and produce relevant data models.
– Ability to work across the organisation to recognise opportunities for the reuse and alignment of data models.
– Ability to solve problems with the most appropriate actions providing co-ordination of teams to implement solutions.
– Can use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts, collaborating with others as appropriate.
– Have a clear understanding of the technical concepts required for the role and how these fit in the wider technical landscape.
– Ability to review requirements, define test conditions, identify issues and risks and analyse and report test activities.
Desirable Skills:
– Data Engineering Certifications (e.g., Cloudera, Databricks)
– Data-related Certifications (e.g., Microsoft Certified: Data Scientist Associate, Databricks Certified Data Engineer)
– Experience with Google Cloud Platform for data and analytics.
– Ability to design an appropriate metadata repository, improve existing repositories, understand a range of tools to manage metadata and advise team members on metadata management.
If you would like to hear more about this opportunity please get in touch.
Responsibilities:
– Lead the design and implementation of scalable, reliable data pipelines and data platforms in the Google Cloud Platform.
– Collaborate with data scientists, analysts, and other engineering teams to define data requirements and optimize data workflows.
– Oversee the deployment and integration of data systems on the Google Cloud Platform.
– Ensure the security, compliance, and performance of Google Cloud Platform data solutions.
– Drive best practices in cloud-based data engineering, automation, and DevOps for data solutions.
– Mentor and guide Senior Data Engineers, contributing to team skill growth and knowledge sharing.
Essential Skills:
– Master’s Degree in Computer Science, Engineering, Information Technology, or related field.
– Cloud Platform Certification (AWS, Azure, or Google Cloud Platform)
– AWS Certified Data Analytics – Specialty
– Google Professional Data Engineer
– Microsoft Certified: Azure Data Engineer
– Experience in cloud platform as a service (PaaS).
– Ability to communicate between technical and non-technical stakeholders, managing expectations and supporting difficult discussions.
– Ability to support teams to apply a range of techniques for data profiling, undertake source system analysis and bring multiple data sources together.
– Can establish enterprise-scale data integration procedures across the data development life cycle.
– Ability to manage resources to ensure that data services work effectively.
– Can identify areas of innovation in data tools and techniques.
– Ability to establish and maintain standards, remaining informed of industry best practice.
– Can understand concepts and principles of data modelling and produce relevant data models.
– Ability to work across the organisation to recognise opportunities for the reuse and alignment of data models.
– Ability to solve problems with the most appropriate actions providing co-ordination of teams to implement solutions.
– Can use agreed standards and tools to design, code, test, correct and document moderate-to-complex programs and scripts, collaborating with others as appropriate.
– Have a clear understanding of the technical concepts required for the role and how these fit in the wider technical landscape.
– Ability to review requirements, define test conditions, identify issues and risks and analyse and report test activities.
Desirable Skills:
– Data Engineering Certifications (e.g., Cloudera, Databricks)
– Data-related Certifications (e.g., Microsoft Certified: Data Scientist Associate, Databricks Certified Data Engineer)
– Experience with Google Cloud Platform for data and analytics.
– Ability to design an appropriate metadata repository, improve existing repositories, understand a range of tools to manage metadata and advise team members on metadata management.
If you would like to hear more about this opportunity please get in touch.
