Head of Data Engineering

Forsyth Barnes
London
3 weeks ago
Applications closed

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Title: Head of Data Engineering Industry: FinTechLocation: London Salary: Up to £140,000 Seeking an experienced Headof Data Engineering to lead data strategy, architecture, and teammanagement in a fast-paced fintech environment. This role involvesdesigning scalable Apache Spark, Databricks, and Snowflakesolutions on Azure, optimizing ETL/ELT pipelines, ensuring datasecurity and compliance, and driving innovation in big dataprocessing. The ideal candidate has 8+ years of data engineeringexperience, strong leadership skills, and deep expertise incloud-based data infrastructure. Key Responsibilities: - DataStrategy & Architecture: Define and implement the overall dataengineering strategy, ensuring scalable, efficient, and secure datapipelines in a fintech environment. - Leadership & TeamManagement: Lead and mentor a team of data engineers, fostering aculture of innovation, collaboration, and best practices. - BigData Processing: Architect, optimize, and manage big data solutionsleveraging Apache Spark, Databricks, and Snowflake to enablereal-time and batch data processing. - Cloud Data Infrastructure:Oversee the deployment and maintenance of Azure-based dataplatforms, ensuring high availability, security, andcost-efficiency. - Data Governance & Compliance: Ensure dataintegrity, security, and compliance with industry regulations(e.g., GDPR, PCI-DSS). - Collaboration with Stakeholders: Workclosely with product, analytics, and engineering teams to deliverdata-driven insights and support business growth. - ETL & DataPipeline Management: Design, implement, and optimize ETL/ELTworkflows using modern cloud technologies. - PerformanceOptimization: Drive continuous improvement in data infrastructureperformance, scalability, and cost-effectiveness. - Innovation& Best Practices: Stay ahead of emerging technologies andmethodologies in data engineering, ensuring fintech-specificinnovation. - Incident & Risk Management: Identify risks,troubleshoot issues, and implement proactive monitoring andincident response mechanisms. Key Requirements: - Experience: 8+years in data engineering, with at least 3+ years in a leadershiprole within fintech or financial services. - Strong hands-onexperience with Apache Spark, Databricks, Snowflake, and Azure DataServices (Azure Data Lake, Azure Synapse, etc.). - Deepunderstanding of distributed computing, data warehousing, and datalake architectures. - Proficiency in Python, SQL, and Scala fordata engineering tasks. - Experience building and optimizingETL/ELT pipelines in a cloud environment. - Leadership &Strategy: Proven ability to build, scale, and managehigh-performing data engineering teams. - Fintech Domain Knowledge:Strong understanding of financial data models, regulatoryrequirements, and security best practices. - DevOps & CI/CD:Experience with infrastructure-as-code (e.g., Terraform) and CI/CDfor data pipelines. - Problem-Solving & Innovation: Ability todrive innovation and optimize data engineering workflows forperformance and cost efficiency. - Communication Skills: Ability toarticulate complex data concepts to both technical andnon-technical stakeholders. #J-18808-Ljbffr

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