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Senior Data Engineer (Cloud Lakehouse)

FDJ UNITED
London, GBR
Full-time
Senior · 5+ years experience
Hybrid
Discovered 3 days ago
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Full Job Posting

Key Responsibilities

  • Data Platform & Architecture
  • Develop and maintain robust and efficient data solutions and products including data transformation, data modelling, and reporting on both on-premises and cloud environments
  • Build modern data lake/lakehouse architectures that support scalable, flexible data processing
  • Enhance platform integration by leveraging domain events to enable more efficient and real-time data processing
  • Self-Service Analytics & Enablement
  • Champion the adoption of generative AI features such as Amazon Q and Copilot to deliver intuitive analytics experiences
  • Build sophisticated solutions to deliver actionable insights, with a strong focus on performance, scalability, and data accessibility
  • Engineering Excellence & Automation
  • Enhance data engineering processes through automation, implementing CI/CD pipelines, and optimizing ETL/ELT flows to improve efficiency and maintainability
  • Be a champion of best development practices on existing and new technologies
  • Collaborate with cross-functional teams to translate business requirements into technical solutions, documenting them as GAPs and aligning them with Architects
  • Data Governance & Discovery
  • Facilitate data discovery and enhance data management processes using platforms like Open Metadata
  • Ensure KPIs and documentation remain accurate and up to date
  • Support data quality and compliance standards across the organization
  • Innovation & Operations
  • Initiate and experiment with new ideas and approaches that support the A&I department's strategy
  • Proactively support and maintain data products, including handling release management, troubleshooting incidents, and providing on-call support as necessary
  • 5+ years of experience in data engineering, with demonstrated expertise in designing and implementing scalable, flexible modern data architectures
  • Experience building modern data lake/lakehouse architectures (e.g., Apache Iceberg) in cloud environments
  • Strong knowledge of AWS (S3, Redshift) or Azure data services
  • Experience with ETL/ELT processes and data ingestion
  • Proven expertise using transformation tools such as dbt
  • Experience with data pipeline orchestration tools (such as Apache Airflow)
  • Experience with best practices applied to data (e.g., testing, CI/CD)
  • Experience developing dashboards and reporting solutions using data visualization tools such as Power BI or Amazon QuickSight
  • Experience with generative AI applications in data analytics
  • Nice to have some JAVA experience
  • We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.

Skills, Knowledge & Experience

  • Required
  • 5+ years of experience in data engineering, with demonstrated expertise in designing and implementing scalable, flexible modern data architectures
  • Experience building modern data lake/lakehouse architectures (e.g., Apache Iceberg) in cloud environments
  • Strong knowledge of AWS (S3, Redshift) or Azure data services
  • Experience with ETL/ELT processes and data ingestion
  • Proven expertise using transformation tools such as dbt
  • Experience with data pipeline orchestration tools (such as Apache Airflow)
  • Experience with best practices applied to data (e.g., testing, CI/CD)
  • Advantageous
  • Experience developing dashboards and reporting solutions using data visualization tools such as Power BI or Amazon QuickSight
  • Experience with generative AI applications in data analytics
  • Nice to have some JAVA experience
  • We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.

Qualifications

  • Experience with ETL/ELT processes and data ingestion
  • Experience with data pipeline orchestration tools (such as Apache Airflow)
  • Experience with best practices applied to data (e.g., testing, CI/CD)
  • Experience with generative AI applications in data analytics

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