Title: Head of Data Engineering
Industry: FinTech
Location: London
Salary: Up to £140,000
Seeking an experienced Head of Data Engineering to lead data strategy, architecture, and team management in a fast-paced fintech environment. This role involves designing scalable Apache Spark, Databricks, and Snowflake solutions on Azure, optimizing ETL/ELT pipelines, ensuring data security and compliance, and driving innovation in big data processing. The ideal candidate has 8+ years of data engineering experience, strong leadership skills, and deep expertise in cloud-based data infrastructure.
Key Responsibilities:
* Data Strategy & Architecture: Define and implement the overall data engineering strategy, ensuring scalable, efficient, and secure data pipelines in a fintech environment.
* Leadership & Team Management: Lead and mentor a team of data engineers, fostering a culture of innovation, collaboration, and best practices.
* Big Data Processing: Architect, optimize, and manage big data solutions leveraging Apache Spark, Databricks, and Snowflake to enable real-time and batch data processing.
* Cloud Data Infrastructure: Oversee the deployment and maintenance of Azure-based data platforms, ensuring high availability, security, and cost-efficiency.
* Data Governance & Compliance: Ensure data integrity, security, and compliance with industry regulations (e.g., GDPR, PCI-DSS).
* Collaboration with Stakeholders: Work closely with product, analytics, and engineering teams to deliver data-driven insights and support business growth.
* ETL & Data Pipeline Management: Design, implement, and optimize ETL/ELT workflows using modern cloud technologies.
* Performance Optimization: Drive continuous improvement in data infrastructure performance, scalability, and cost-effectiveness.
* Innovation & Best Practices: Stay ahead of emerging technologies and methodologies in data engineering, ensuring fintech-specific innovation.
* Incident & Risk Management: Identify risks, troubleshoot issues, and implement proactive monitoring and incident response mechanisms.
Key Requirements:
* Experience: 8+ years in data engineering, with at least 3+ years in a leadership role within fintech or financial services.
* Strong hands-on experience with Apache Spark, Databricks, Snowflake, and Azure Data Services (Azure Data Lake, Azure Synapse, etc.).
* Deep understanding of distributed computing, data warehousing, and data lake architectures.
* Proficiency in Python, SQL, and Scala for data engineering tasks.
* Experience building and optimizing ETL/ELT pipelines in a cloud environment.
* Leadership & Strategy: Proven ability to build, scale, and manage high-performing data engineering teams.
* Fintech Domain Knowledge: Strong understanding of financial data models, regulatory requirements, and security best practices.
* DevOps & CI/CD: Experience with infrastructure-as-code (e.g., Terraform) and CI/CD for data pipelines.
* Problem-Solving & Innovation: Ability to drive innovation and optimize data engineering workflows for performance and cost efficiency.
* Communication Skills: Ability to articulate complex data concepts to both technical and non-technical stakeholders.
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