Senior Data Engineer

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.
You’ll design, build and maintain data pipelines using a medallion architecture, transforming operational data into trusted, well-structured datasets for reporting and analysis.
The role combines hands-on development, data modelling, production support and technical leadership. You’ll work closely with development and data teams, product owners and business stakeholders to deliver reliable data products that meet reporting and operational needs.
Responsibilities
Work with analysts and stakeholders to understand source systems, data flows, business processes and reporting requirements, clarifying business rules and challenging unclear assumptions.
Design, build and maintain ETL/ELT pipelines in Azure Databricks using Python, PySpark and SQL.
Implement bronze, silver and gold data layers, covering raw data ingestion, cleansing, validation and preparation for reporting.
Develop curated datasets and dimensional models, and make them available through Microsoft Fabric for Power BI reporting.
Implement incremental processing and manage schema changes, duplicates, missing values and late-arriving data.
Provide technical guidance and mentoring, lead code and design reviews, and support consistent development, testing and CI/CD practices.
Contribute to product and delivery discussions by explaining technical trade-offs, identifying data dependencies and helping prioritise work based on business value and technical constraints.
Document data models, transformations, lineage, dependencies and operational procedures.
7+ years of experience in data engineering, including designing, building, deploying and supporting production data pipelines.
Strong Python and SQL skills, with strong hands-on experience using PySpark and Spark SQL in Azure Databricks.
Experience with Microsoft Fabric, particularly making curated data available for reporting through OneLake, lakehouses or warehouses.
Good understanding of data warehousing and dimensional modelling, including table grain, facts, dimensions and historical changes.
Experience orchestrating and monitoring data pipelines.
Experience with automated testing, data validation, Git and CI/CD practices.
Working knowledge of Azure storage, access management and secure credential handling.
Taking ownership of technical decisions, reviewing designs and code, and guiding other engineers.
Ability to understand business processes and product priorities, translate requirements into practical data solutions, and explain how technical choices affect users, reporting and operational decisions.
Ability to work independently, explain technical decisions clearly and collaborate effectively in English with business and technical colleagues.
Useful additional experience
Experience with Snowflake.
Experience delivering data solutions in enterprise environments. Familiarity with logistics, transportation or supply chain data is an advantage.
Enterprise data modelling and aligning data definitions across source systems.
Practical use of AI development tools.

Skills
Python, Git, Azure, CI/CD, SQL, Snowflake, Databricks, Automation Testing, Machine Learning, Artificial Intelligence

Experience
7+ yrs

Employment type
Full-time

Work arrangement
Hybrid