Job Title: Head of Data Engineering
Location: Remote
Industry: Consultancy
Salary: £90,000 - £100,000
Company Overview:
Forsyth Barnes are excited to be working with a leading Managed Service Provider, specialising in delivering comprehensive IT solutions to clients across various industries
Job Description:
They are seeking a talented and experienced Head of Data Engineering to lead our data engineering team at the MSP. In this role, you will be responsible for overseeing the design, development, and implementation of data solutions that support our clients' business needs and contribute to the overall success of our managed services offerings.
Key Responsibilities:
Lead and manage a team of data engineers and data architects in designing, constructing, and maintaining data pipelines, ETL processes, and data warehousing solutions.
Collaborate with clients and internal stakeholders to define data requirements, develop data strategies, and deliver data-driven solutions that align with business objectives.
Drive innovation and continuous improvement in data engineering practices, technologies, and tools to ensure scalability, performance, and reliability of data infrastructure.
Establish data governance policies, best practices, and standards to ensure data quality, security, and regulatory compliance for client data environments.
Work closely with cross-functional teams, including data scientists, analysts, and IT experts, to integrate data sources, optimize data workflows, and support AI/ML initiatives.
Provide technical leadership, guidance, and mentorship to the data engineering team, fostering a culture of collaboration, innovation, and professional development.
Qualifications:
Bachelor's or master's degree in computer science, Information Technology, Data Engineering, or a related field.
Proven experience in data engineering, data architecture, or a similar role, with a strong background in leading data initiatives and managing data engineering teams.
Expertise in data processing technologies, such as Apache Hadoop, Spark, Kafka, or similar tools for large-scale data processing and analytics.
Proficiency in database systems, data modeling, ETL tools, data integration techniques, and cloud data platforms (e.g., AWS, Azure, GCP).
Familiarity with data governance, data security, and regulatory compliance requirements in a managed services environment.
Strong leadership skills, project management capabilities, and the ability to effectively communicate with stakeholders at all levels
