Data Engineer (Python & SQL)
Role details
Job location
Tech stack
Job description
An AI first SaaS business that transforms high quality first party data into trusted, decision ready insight at scale is looking for a Senior Data Engineer to join its growing data and engineering team.
This role sits at the core of data engineering. You will work with data that is often imperfect and transform it into well structured, reliable datasets that other teams can depend on. The focus is on engineering high quality data foundations rather than analytics or cloud infrastructure alone.
You will design and build clear, maintainable data pipelines using Python and SQL within a modern data and AI platform, with a strong focus on data quality, robustness, and long term reliability.
You will also play an important mentoring role within the team, supporting and guiding other data engineers and helping to raise engineering standards through thoughtful, hands on leadership.
Why join ·A supportive and inclusive environment where different perspectives are welcomed and people are encouraged to contribute and be heard ·Clear progression with space to deepen your technical expertise and grow your confidence at a sustainable pace ·A team that values collaboration, good communication, and shared ownership over hero culture ·The opportunity to work on meaningful data engineering problems where quality genuinely matters
What you will be doing ·Designing and building cloud based data and machine learning pipelines that prepare data for analytics, AI, and product use ·Writing clear, well-structured Python, PySpark, and SQL to transform and validate data from multiple upstream sources ·Taking ownership of data quality, consistency, and reliability across the pipeline lifecycle ·Shaping scalable data models that support a wide range of downstream use cases ·Working closely with Product, Engineering, and Data Science teams to understand data needs and constraints ·Mentoring and supporting other data engineers, sharing knowledge and encouraging good engineering practices ·Contributing to the long term health of the data platform through thoughtful design and continuous improvement
Requirements
·Strong experience using Python and SQL to transform large, real world datasets in production environments ·A deep understanding of data structures, data quality challenges, and how to design reliable transformation logic ·Experience working with modern data platforms such as Azure, GCP, AWS, Databricks, Snowflake, or similar ·Confidence working with imperfect data and making it fit for consumption downstream ·Experience supporting or mentoring other engineers through code reviews, pairing, or informal guidance ·Clear, thoughtful communication and a collaborative mindset
You do not need to meet every requirement listed. What matters most is strong, hands on experience using Python and SQL to work confidently with complex, real world data, apply sound engineering judgement, and help others grow through your experience.
