Develop and maintain ETL workflows using SQL Server Integration Services (SSIS) to extract, transform and load data from multiple source systems into the enterprise data warehouse.
Work closely with data scientists, business analysts and other stakeholders to understand their data requirements and translate them into technical specifications and data models.
Lead the design, development, and implementation of the Domain Group Data Store as the central source for data collection, storage, integration, and distribution.
Ensures the data integrity and quality.Develop, maintain and optimize data pipelinesWork with stakeholders including the Product, Business and Analytic teams to assist with data-related issues and support their data transformation requirements.BS/MS/PhD in IT, Mathematics, Science or Engineering discipline Up to 5+ yrs relevant experience beyond first degreeExperience with one of the following languages: Python, R, Java, C/C++ and Scala.Familiar with data ETL from a wide variety of data sources.Experience with SQL and NoSQL databases.Experience with pipeline and workflow management tools.Experience with various messaging and stream processing.Experience with object-oriented/object function scripting languages.Familiar with containerisation and orchestration tools.Familiar with one of the following cloud-based services: GCP, AWS or Azure and its tools and services.Ability to work under pressure and change, and balance among speed, reliability, interpretability.Good working knowledge of productivity tools such as G Suite, Git, Jira, Confluence.Experience with code versioning, code review and documentation.Proficient understanding of distributed computing principles.Able to select and integrate big data tools and frameworks.Familiar or prone to adopt design thinking methods.Openness to experimenting with new techniques and new ways of working.
Extensive full life-cycle expertise (requirements → design → development → testing → deployment) in modern data warehousing, including ETL/ELT development, CI/CD automation, enterprise data integration, dimensional and relational data modelling, data domain architecture, data lake analytics, Apache Iceberg tables, Control‑M scheduling, and enterprise BI solutions.