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    • Data Engineer Expert/Manager Consulting · · - United Kingdom - Dufrain

    Dufrain
    Dufrain United Kingdom

    1 month ago

    Default job background
    Description

    We are Dufrain, a pure-play data consultancy that helps businesses unlock the true value of their data by providing market-leading data solutions and services. Our expertise includes developing strategies for AI readiness, improving data literacy, and enhancing real-time reporting.

    Our Microsoft Data Engineering Practice delivers end-to-end data platforms and engineering pipelines across Microsoft Fabric, Azure Synapse Analytics, and Azure Data Bricks. We provide strategic guidance and governance support across various industries.

    Job Role

    As an expert Data Engineer Consultant, you'll play a pivotal role in shaping Data Engineering strategy, mentoring and managing delivery teams, driving platform adoption, and ensuring high-quality outcomes for our clients. This is an exciting opportunity for experienced consultants who thrive on variety and strategic work, while also being hands-on with all aspects of Data Engineering.

    Key Responsibilities

    • Lead end-to-end Data Engineering solution delivery on complex engagements, ensuring technical excellence and business value.
    • Mentor and guide Data Engineering teams, fostering a culture of knowledge sharing, continuous improvement, and high-quality delivery.
    • Own and drive pre-sales engagements, collaborating with sales teams to develop compelling proposals and solutions.
    • Ensure best practices in data engineering, governance, security, and compliance.
    • Collaborate closely with clients to understand their business needs and translate them into robust technical solutions.
    • Act as a subject matter expert in Microsoft Fabric, advising both internal teams and clients on best practices and strategic implementations.
    • Conduct technical presentations, demonstrations, and workshops to showcase solutions to potential clients.
    • Foster a culture of innovation, collaboration, and continuous improvement within the team.
    • Facilitate requirements workshops and design sessions, engaging both technical and non-technical stakeholders to co-create solutions.
    • Support revenue generation and brand building activity, including presenting demos to external stakeholders and scoping client needs to support the commercial process.
    • Own and drive delivery plans, structuring high-quality work, managing risks and dependencies, and communicating effectively with senior stakeholders to ensure alignment with strategic goals.

    Requirements

    To succeed in this role, you'll need:

    • Proven experience in Data Engineering, with hands-on expertise with Spark and Microsoft Fabric.
    • Strong leadership skills, with experience managing teams in a consulting or enterprise environment.
    • Ability to drive and lead pre-sales discussions, including solution design, estimation, and proposal writing.
    • Extensive experience in designing and implementing data pipelines, data lakes, and data warehouses.
    • Strong knowledge of ETL processes, data modelling, and cloud-based solutions.
    • Excellent stakeholder management and communication skills.
    • Experience working with Azure Data Services, SQL, Python, and/or other relevant technologies.
    • Ability to thrive in a fast-paced environment and manage multiple projects simultaneously.

    Desirable Qualifications

    • Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
    • Microsoft Certified: Fabric Data Engineer Associate (DP-700)
    • Databricks Data Engineer Associate
    • Databricks Data Engineer Professional

    What's Next

    If you're passionate about data and looking to join a leading data and analytics company based in the UK, we encourage you to submit your CV highlighting your relevant experience and certifications. Please note that applicants must have the right to work in the UK and not require sponsorship now or in the future. Visa sponsorship is not available.

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