{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “Data Engineering – Senior Consultant in London”, “description”: “
Senior Consultant – Data Engineering
As a senior consultant in the Business Transformation team, you will design and deliver data solutions using modern cloud-based platforms and advise clients on their data landscape, shaping data strategies and roadmaps.
Key Responsibilities
- Facilitate requirements gathering workshops across business areas to agree objectives, use cases, and data needs.
- Support the development of data solutions that align initiatives to business objectives, balancing best practice ways of working with clients’ requirements.
- Provide guidance on data governance and strategies, including advising on recommended frameworks and policies to enable clients to increase their data maturity.
- Manage delivery across multiple workstreams and engagements, support junior team members, and apply structured engineering practices across the team.
- Design, build, and optimise end‑to‑end data pipelines (ingestion, transformation, orchestration) using SQL and Python, focusing on reliability, maintainability and performance.
- Participate in and lead client engagements, facilitating workshops, confirming objectives, and developing delivery plans and budgets.
Qualifications & Experience
- Strong understanding of Azure data services and integration systems (eg, Azure Data Factory, Azure Data Lake) and how they complement Fabric/Databricks.
- Experience implementing platform security practices (secure connectivity to sources, secrets management, role‑based access concepts) aligned to client policies.
- Experience in formal data quality assessments and defining reconciliation approaches with business stakeholders.
- Client‑facing data engineering experience (3+ years) in a professional services environment, including leading requirements workshops with clients.
- Hands‑on engineering capability across Microsoft Fabric and Azure Databricks, with SQL and Python experience to design and build scalable data solutions; background in PySpark desirable.
- Experience in proposal writing and business development, supporting bids and client presentations.
- Relevant certifications (desirable): Azure Data Engineer / Fabric Data Engineer or Analytics Engineer, Databricks fundamentals.
- Strong academic record; preferably a relevant degree (computer science, software engineering, data engineering, data analytics, or information systems).
- Minimum of 4 years’ work experience, ideally within a professional services environment, delivering data engineering and/or data platform engagements.
- Understanding SQL Server Databases, SQL Server Integration Services (SSIS), Azure Data Resources, Azure Data Factory, Azure Data Lake, Azure Databricks, and Azure Analysis Services.
- Strong engineering practices: version control (Git), CI/CD for data and platform artefacts, and disciplined release management via Azure DevOps (ADO).
- Experience implementing data quality controls and validation checks, and producing clear documentation to support traceability, handover and adoption.
- Good communication and presentation skills, with the ability to explain complex ideas to non‑technical stakeholders.
- Effective project management skills and the ability to meet deadlines while working on multiple projects simultaneously.
- Create high‑quality, client‑facing document outputs.
- London‑based or willing to travel to London fortnightly.
Benefits
- Hybrid and flexible working.
- 26 days holiday, with optional additional days.
- Lifestyle, health, and wellbeing support, including financial wellbeing benefits, electric car scheme, and access to a virtual GP.
- Access to a suite of 300+ on‑demand courses developed by the in‑house Talent Development team.
Company: Energy Jobline CVL
Location: London
Job Description:
Senior Consultant – Data Engineering
As a senior consultant in the Business Transformation team, you will design and deliver data solutions using modern cloud-based platforms and advise clients on their data landscape, shaping data strategies and roadmaps.
Key Responsibilities
- Facilitate requirements gathering workshops across business areas to agree objectives, use cases, and data needs.
- Support the development of data solutions that align initiatives to business objectives, balancing best practice ways of working with clients’ requirements.
- Provide guidance on data governance and strategies, including advising on recommended frameworks and policies to enable clients to increase their data maturity.
- Manage delivery across multiple workstreams and engagements, support junior team members, and apply structured engineering practices across the team.
- Design, build, and optimise end‑to‑end data pipelines (ingestion, transformation, orchestration) using SQL and Python, focusing on reliability, maintainability and performance.
- Participate in and lead client engagements, facilitating workshops, confirming objectives, and developing delivery plans and budgets.
Qualifications & Experience
- Strong understanding of Azure data services and integration systems (eg, Azure Data Factory, Azure Data Lake) and how they complement Fabric/Databricks.
- Experience implementing platform security practices (secure connectivity to sources, secrets management, role‑based access concepts) aligned to client policies.
- Experience in formal data quality assessments and defining reconciliation approaches with business stakeholders.
- Client‑facing data engineering experience (3+ years) in a professional services environment, including leading requirements workshops with clients.
- Hands‑on engineering capability across Microsoft Fabric and Azure Databricks, with SQL and Python experience to design and build scalable data solutions; background in PySpark desirable.
- Experience in proposal writing and business development, supporting bids and client presentations.
- Relevant certifications (desirable): Azure Data Engineer / Fabric Data Engineer or Analytics Engineer, Databricks fundamentals.
- Strong academic record; preferably a relevant degree (computer science, software engineering, data engineering, data analytics, or information systems).
- Minimum of 4 years’ work experience, ideally within a professional services environment, delivering data engineering and/or data platform engagements.
- Understanding SQL Server Databases, SQL Server Integration Services (SSIS), Azure Data Resources, Azure Data Factory, Azure Data Lake, Azure Databricks, and Azure Analysis Services.
- Strong engineering practices: version control (Git), CI/CD for data and platform artefacts, and disciplined release management via Azure DevOps (ADO).
- Experience implementing data quality controls and validation checks, and producing clear documentation to support traceability, handover and adoption.
- Good communication and presentation skills, with the ability to explain complex ideas to non‑technical stakeholders.
- Effective project management skills and the ability to meet deadlines while working on multiple projects simultaneously.
- Create high‑quality, client‑facing document outputs.
- London‑based or willing to travel to London fortnightly.
Benefits
- Hybrid and flexible working.
- 26 days holiday, with optional additional days.
- Lifestyle, health, and wellbeing support, including financial wellbeing benefits, electric car scheme, and access to a virtual GP.
- Access to a suite of 300+ on‑demand courses developed by the in‑house Talent Development team.
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Posted: May 20th, 2026