Senior Data Engineer

TL;DR

Senior Data Engineer (Data Engineering): Design, build, and run reliable data pipelines and services for large-scale search and analytics use cases with an accent on batch and ELT/ETL workflows, distributed systems, and cloud reliability. Focus on engineering production-grade ingestion and processing systems using Python, Java, Spark, SQL, Airflow, and AWS while collaborating with product, platform, and data science partners.

Location: London Wall

Company

hirify.global builds information and analytics products that support research and healthcare.

What you will do

• Design, build, and maintain scalable data pipelines and services.
• Develop batch and ELT/ETL workflows to ingest and process large datasets.
• Implement data workflows using Python, Java, Spark, SQL, and Airflow.
• Apply software engineering practices including testing, documentation, and CI/CD.
• Contribute to AWS-based systems with a focus on reliability, monitoring, and automation.
• Collaborate with product, platform, and data science partners; support engineers via code reviews and knowledge sharing.

Requirements

• Experience as a data or software engineer on production systems.
• Strong Python skills and experience with at least one backend language (e.g., Java).
• Understanding of data engineering concepts such as data lakes, batch processing, and distributed systems.
• Experience building or operating data pipelines with tools like Spark and Airflow.
• Familiarity with cloud platforms (AWS preferred) and production monitoring.
• Clear communication skills and a collaborative approach to problem-solving.

Culture & Benefits

• Healthy work/life balance and flexible working hours.
• Comprehensive pension plan.
• Generous vacation entitlement with option for sabbatical leave.
• Family leave options including maternity, paternity, adoption, and family care leave.
• Personal Choice budget and employee assistance program (global).

Hiring process

• Interviews to assess experience with production data engineering and collaboration.
• Discussion of how engineering practices (testing, CI/CD, monitoring) are applied in real systems.