Lead Data Engineer

Lloyd's List

Lloyd's List delivers crucial maritime insights, utilizing data and advanced analytics to serve over 60,000 global professionals. The company’s data is sourced from credible partners, supporting maritime operations. The Lead Data Engineer will join a dynamic team to innovate and maintain data systems, ensuring system reliability and efficiency.

In this role you can expect to have the responsibilities:

• Collaborate with product teams to ensure raw data is clean and usable.
• Lead specialist PODs for product innovation.
• Explore and champion new technologies.
• Maintain and innovate AWS cloud infrastructure systems.
• Work with SQL and various data repository platforms.
• Maintain machine learning and AI models.
• Create next-generation data ingestion platforms.
• Resolve conflicts and manage data feed uptimes.
• Produce technical documentation and support product development.

This role comes with the following benefits:

• 25 Days Holiday, increasing to 27 after 2 years, plus a birthday day off.
• Work anywhere policy up to 4 weeks per year.
• Life Assurance at 4x salary.
• Pension scheme with 5% employer match.
• Paid volunteering days.
• Healthy Lifestyle Subsidy.
• Enhanced Family Leave.
• Flexible benefits including Private Healthcare.

This role requires you to have:

• At least 4 years' experience as a Data Engineer.
• Proficient in Python, AWS, and SQL/Oracle.
• Experience with ETL processes and flat file data models.
• Strong data mining and analytical skills.
• Familiarity with BI capabilities and data structures.
• Understanding of micro-services and data technologies.
• Strong problem-solving and quantitative analysis skills.
• Excellent verbal and written communication.

You would benefit from having:

• Experience with C#, C++, Java.
• Experience in streaming and real-time data processing.
• Familiarity with SAS Analytics platform.

Lloyd's List values diversity and inclusivity and encourages applications from all backgrounds. They are an Equal Opportunity Employer, supporting adjustments for candidates to perform at their best.