Senior Data Engineer (AI)

Location: London, United Kingdom; hybrid

Company

hirify.global is a data-driven organisation using data platforms to support analytics, reporting, data science, innovation, and strategic growth.

What you will do

• Lead the development and optimisation of ingestion and transformation pipelines using Spark, Scala, Python, AWS, DBT, and Snowflake.
• Architect and evolve a robust, scalable, secure, and future-ready Data Lake environment.
• Own ETL processing, table refreshes, defect resolution, and BAU activities while driving automation to reduce manual effort.
• Improve performance through concurrency, multi-threading, automation, and best-practice engineering patterns.
• Guide Agile delivery, mentor engineers, and ship high-quality cloud-native data solutions through CI/CD.
• Integrate multiple data sources and influence data engineering standards, patterns, and governance.

Requirements

• Hands-on experience using DBT to design, build, and improve data transformations in a complex data environment.
• Engineering experience with Python and SQL, including solving complex data problems at scale.
• Ability to design and guide modern data engineering solutions, with knowledge of data modelling, ETL/ELT, data warehousing, and scalable data pipelines.
• Ability to lead and develop Data Engineers through hands-on technical contribution, coaching, technical direction, and delivery ownership.
• Interest in AI and automation, with technical curiosity about improving engineering quality, productivity, and ways of working.
• Strong data engineering foundations and hands-on DBT experience are encouraged even when not every listed technology is covered.

Nice to have

• Experience with AWS or another major cloud platform; the environment includes EMR, Athena, Lambda, S3, Glue, and Step Functions, with transferable experience accepted.
• Experience with Snowflake, Spark, Scala, or Airflow, or comparable technologies and data engineering challenges.
• Experience with Git, GitHub, and CI/CD practices, including GitHub Actions.
• Knowledge of real-time data processing, data governance, data quality, or observability.
• Experience using AI-enabled engineering tools or automation to improve productivity, quality, or reliability.

Culture & Benefits

• Permanent, full-time employment in a hybrid role.
• Inclusive equal-opportunity culture supporting diversity and accessibility.
• Reasonable adjustments are available for disabilities or caring responsibilities during the application and interview process.