Job Purpose

We are seeking a Senior Data Engineer to own and evolve our data platforms, driving the design and delivery of scalable, cloud-native data solutions. This role will oversee the development and optimisation of automated data workflows and reporting systems across the business, ensuring the reliability and growth of our data infrastructure.

The successful candidate will combine deep technical expertise in Python, SQL, and modern cloud technologies — particularly Microsoft Fabric — with leadership skills to mentor and guide other engineers. They will play a pivotal role in migrating legacy KNIME workflows into modern architectures, building robust lakehouse environments, and establishing best practices in automation and orchestration.

This is a strategic, hands-on role that blends technical leadership with platform ownership. It offers significant autonomy, direct impact on business-critical functions, and the opportunity to shape the future of data engineering within the organisation.

Main Duties & Responsibilities

• Own the design, build, and optimisation of cloud-based data lakehouse environments to support analytics and reporting at scale
• Lead the development and maintenance of Python-based ETL/ELT pipelines to monitor systems, ensure data quality, and proactively flag issues
• Oversee the design and management of Microsoft Fabric solutions, including Lakehouses, Pipelines, and Dataflows
• Translate high-level business requirements into scalable, actionable workflows and reporting solutions, working closely with Finance and other key stakeholders
• Drive the migration of legacy processes into modern Python and SQL-based architectures
• Establish and own automation/orchestration frameworks using tools such as Dagster, Apache Airflow, Prefect, or Azure Data Factory
• Coach, mentor, and guide junior data engineers, ensuring best practices, knowledge sharing, and skills development
• Take ownership of data engineering roadmaps, ensuring delivery, scalability, and alignment with business needs

Personal Qualities

• Can-do attitude — prepared to "go the extra mile"
• Lots of energy — a team player who can work off their own initiative
• Heightened sense of urgency
• Curious learner with an interest in professional development
• Actively demonstrates a passion for the business
• Strong leadership skills, with the ability to coach, mentor, and develop junior data engineers
• Excellent communication and collaboration skills, able to translate complex technical concepts for non-technical stakeholders and influence senior decision-makers
• Strategic mindset with the ability to balance hands-on delivery and long-term platform ownership
• Ambassador of corporate values

Key Attitudes/Behaviours

Exceptional results require exceptional people. Exceptional people who live and breathe the plan.com values. We are built on trust, fuelled by passionand driven by excellence.

Attributes we look for include:

• Curious and continuous learner – We value individuals who are eager to learn and grow and committed to self-improvement. We encourage continuous learning and provide a wide range of opportunities for personal and professional development.
• Innovative and Initiative – We embrace innovation and encourage our team members to be ambitious, think outside the box, challenge the status quo, and explore new ideas to drive growth and success. We value team players who can work off their own initiative, empower our people to make informed decisions and trust them to do the right thing.
• Adaptable – In a dynamic industry, adaptability is key. We seek individuals who can thrive in a changing environment, embrace new challenges, and quickly adjust to evolving circumstances while maintaining a positive attitude.
• Collaborative – We value the collective power of working together.
• Passion – One of our three core values, passion goes beyond our people's enjoyment of their work. It's a passion for the business and their contribution to furthering its success. It means striving to be the best and encouraging those around us to do the same. And it means not being afraid to take risks. Go big or go home!

Essential Skills

• Advanced Python skills for data transformation (e.g., pandas, polars, SQLAlchemy)
• Strong SQL expertise across varied data sources
• Proven track record in building, deploying, and maintaining complex ETL/ELT workflows at scale
• Experience designing and managing data workflows in financial reporting or other data-intensive contexts
• Demonstrated ability to lead projects, manage priorities, and provide technical guidance to team members
• Proactive ownership mindset with the ability to thrive in a fast-paced, evolving environment

Desirable Skills

• Hands-on experience with Microsoft Fabric (Lakehouses, Pipelines, Dataflows) and exposure to data lake architecture design
• Familiarity with orchestration tools (e.g., Dagster, Airflow, Prefect, Azure Data Factory)
• Exposure to containerisation and DevOps practices (e.g., Docker, Git, Bitbucket)
• Exposure to event streaming platforms like Kafka
• Experience with version control best practices (git, Bitbucket, CI/CD)
• Experience building RESTful APIs (FastAPI, Flask, Django)
• Experience leading migrations from legacy tools (e.g., KNIME, SAS) to modern, cloud-native solutions

• Hands-on experience with Microsoft Fabric (Lakehouses, Pipelines, Dataflows) and exposure to data lake architecture design
• Familiarity with orchestration tools (e.g., Dagster, Airflow, Prefect, Azure Data Factory)
• Exposure to containerisation and DevOps practices (e.g., Docker, Git, Bitbucket)
• Exposure to event streaming platforms like Kafka
• Experience with version control best practices (git, Bitbucket, CI/CD)
• Experience building RESTful APIs (FastAPI, Flask, Django)
• Experience leading migrations from legacy tools (e.g., KNIME, SAS) to modern, cloud-native solutions

• Bachelor's or Master's degree in Engineering, Computer Science, Mathematics/Statistics, or equivalent industry experience
• Substantial experience (5+ years) in data engineering, data architecture, or similar roles, ideally with exposure to financial or data-intensive industries