About the Team and Role 

We are looking for a hands-on Senior Data Engineer with strong data mapping and integration expertise to join our international data engineering function. This role combines deep technical delivery with upstream data analysis and mapping, helping ensure that complex source data is accurately modelled, integrated, and made available to downstream consumers in a consistent and governed way. 

You will work at the intersection of data mapping, data engineering, and data management, collaborating closely with business stakeholders, data analysts, product teams, and other engineers across multiple timezones. The role plays a key part in delivering high‑quality, well‑governed data solutions that underpin digital channels, analytics, and operational reporting. 

Key Responsibilities 

Data Mapping & Analysis 

• Own and deliver source‑to‑target data mappings for inbound and outbound data flows aligned to the enterprise common data model 

• Work with business and technical stakeholders to gather, evaluate, validate, and document data requirements 

• Plan and facilitate mapping workshops, including preparation, gap analysis, follow‑ups, and incorporation of change requests 

• Perform impact analysis on data model and mapping changes and maintain mapping documentation and metadata 

• Validate mapping outcomes using SQL queries and provide data quality feedback and metrics 

• Act as a bridge between data engineering, data governance, and business teams 

Data Engineering & Integration 

• Design, develop, and maintain ETL / ELT processes supporting both project delivery and business‑as‑usual workloads 

• Develop and enhance data pipelines using SQL, SSIS, and/or modern cloud-based tooling 

• Monitor and support production data processes, including batch runs, releases, and issue resolution 

• Troubleshoot complex data and performance issues within relational database environments 

• Contribute to improvements in code quality, performance, tooling, and ways of working 

• Support and evolve data integration patterns as the platform moves towards cloud‑native solutions 

Collaboration & Governance 

• Work within Agile delivery teams, contributing to planning, estimation, and delivery 

• Maintain strong stakeholder relationships and communicate clearly on progress, risks, and dependencies 

• Ensure solutions adhere to data governance, security, and quality standards 

• Contribute to the continual improvement of data management and data engineering practices 

Essential Skills and Experience 

• Minimum 5 years experience in data engineering and data integration roles 

• Proven experience delivering data mapping / source‑to‑target mappings against a common data model 

• Advanced SQL skills, including complex queries, views, stored procedures, and performance tuning 

• Experience building and supporting ETL processes 

• Solid understanding of relational data models, OLTP and OLAP environments 

• Experience working in Agile teams and collaborating with cross‑functional stakeholders 

• Excellent analytical, problem‑solving, and communication skills 

• Ability to work independently, manage multiple priorities, and see work through end‑to‑end 

Desirable / Nice to Have 

• Experience with cloud platforms (AWS and/or Azure) 

• Python, Databricks, or modern data engineering frameworks 

• Experience with metadata or data management tools (e.g. Collibra or similar) 

• Knowledge of source control (Git) and CI/CD pipelines 

• Experience across SQL Server, Oracle, and/or Postgres 

• Exposure to AI‑assisted development or data tooling 

• Experience in regulated or data‑intensive industries (e.g. healthcare, insurance, financial services) 

The Person We’re Looking For 

• A proactive, detail‑oriented engineer who enjoys working from requirements through to production 

• Comfortable operating between business language and technical implementation 

• Confident facilitating workshops and influencing stakeholders 

• Passionate about data quality, structure, and doing things the “right way” 

• Curious, adaptable, and keen to grow with evolving data platforms