IT & Software

Senior Data Engineer

Artefact

London · Greater London · United Kingdom

Overview

As Senior Data Engineer, you will design and run scalable data pipelines and architectures that power data-driven decisions. You’ll lead cross-functional data projects, mentor engineers, and uphold governance and security standards. This role blends hands-on pipeline work with leadership to ensure reliable, high-quality data delivery at scale. You’ll work with modern cloud-native tools to drive transformation and impact across client engagements.

Responsibilities
  • Design, build, and maintain scalable data pipelines using SQL and Python, with Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and PySpark
  • Lead integration of complex data systems ensuring data consistency across platforms
  • Implement CI/CD practices for data pipelines to improve efficiency and quality
  • Collaborate with data architects, analysts, and stakeholders to translate requirements into technical solutions
  • Oversee and mentor a team of data engineers to deliver high-quality projects
  • Develop and enforce data governance, security, and compliance practices
  • Optimize data retrieval and develop dashboards and reports for business teams
  • Continuously evaluate new technologies to enhance data engineering capabilities
Key requirements
  • 3+ years of industry experience in data engineering
  • Strong proficiency in SQL, Python, and big data technologies
  • Experience with cloud-native orchestration tools and distributed processing
  • Experience with Infrastructure as Code (Terraform)
  • Solid understanding of CI/CD, DevOps/DevSecOps
  • Proven leadership experience managing data engineering teams
  • Excellent problem-solving in ambiguous environments
  • Proficient with AI-assisted workflows to boost task efficiency
  • Strong communication and interpersonal skills
  • Understanding of data architecture (data mesh, data lake, data warehouse, data lakehouse)
  • communication
  • leadership
  • problem-solving
  • SQL
  • Python
  • Databricks

Reference: WJ-747_30143060

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