Data Engineer

Our client is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world.

They help lawyers win cases, manage their work more efficiently, serve their clients better and grow their practices. They assist corporations in better understanding their markets, monitoring their brands and competition, and in mitigating business risk. They collaborate with universities to educate students, and support nation-building with governments and courts by making laws accessible and strengthening legal infrastructures. They partner with leading global associations and customers to collect evidence against war criminals and provide tools to combat human trafficking.

Role Overview:

• We are building a new data engineering team to support a strategic move from legacy data estates to a modern data platform built on Databricks. 
• This role plays a key part in re-engineering existing systems, improving scalability, and enabling future innovation.

Responsibilities:

• Lead the transition of legacy data systems to Databricks, ensuring reliability and performance.
• Design, build, and maintain robust, scalable data pipelines to support analytical and operational use cases.
• Collaborate closely with subject matter experts, product teams, and business stakeholders to understand and implement business logic accurately.
• Apply data engineering and programming best practices to ensure high-quality, maintainable, and secure solutions.
• Mentor junior engineers, fostering technical growth and promoting knowledge sharing across the team.
• Participate in code reviews, architectural discussions, and technical decision-making to uphold engineering standards.

Requirements: 

Required Skills & Experience:

• Hands-on experience in software or data engineering roles.
• Strong proficiency in Python and working knowledge of PySpark.
• Experience or strong interest in Databricks.
• Solid understanding of SQL and structured data.
• Experience with cloud platforms (AWS preferred; Azure/GCP acceptable).
• Familiarity with REST APIs and event-driven architectures.
• Experience using Git or similar version control systems.
• Strong problem-solving skills and collaborative mindset.

Preferred Experience:

• Experience working on data platform modernization or migration projects.
• Ability to refactor and improve legacy codebases.
• Exposure to AI/ML data pipelines is an advantage.