Senior Data Engineer
We are seeking a Senior Data Engineer to lead the development of a modern, scalable, and secure data platform that supports enterprise-wide analytics, machine learning, and AI initiatives. The Senior Data Engineer will be responsible for designing, building, maintaining and optimising robust data pipelines and enabling governed data sharing with external partners. This role will work closely with data analysts, data scientists, and AI engineers to ensure the scalable, secure, and high-performance data platforms that power analytics, AI, machine learning and operational excellence required by business teams. You will build data assets to provide robust, compliant and agile solutions to support in healthcare, retail, and insurance innovations.
WHAT WE'RE LOOKING FOR?
Minimum
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
Certification in cloud platform: AWS, Azure Data Engineer (DP-203/DP-700), or Databricks Certified Data Engineer
6+ years of experience in data engineering or software development
3+ years of hands-on experience with Databricks Intelligence Platform and implementing Medallion Architecture.
Strong proficiency in Python, SQL, Spark, and cloud-native data services (e.g., Azure Data Lake, AWS S3, GCP BigQuery)
Familiarity with cloud-native data integration tools (e.g. SAP Datasphere, Snowflake Airflow)
Experience in delivery and collaboration tools: GitHub, JIRA, Confluence and MIRO
Proven experience in developing data platforms that support data science, data analytics and AI workloads
Extensive experience in ETL development and Data Pipelines with CI/CD, as well as data governance, and data quality frameworks
Solid understanding of data science workflows, model lifecycle, and AI concepts
Preferred Qualifications
Certification in Machine Learning or AI (e.g., Azure AI Engineer Associate)
Experience in healthcare, retail, or insurance data ecosystems
Working knowledge of SAP BW, S4 HANA, CRM, ERP, and Data Business Cloud
WHAT YOU WILL BE DOING?
Lead the development and maintenance of a scalable and secure data platform using the Medallion Architecture to support analytics, data science, and AI workloads with high performance and reliability
Build robust, reusable, and modular data pipelines leveraging Python, SQL, Spark, and cloud-native services to ensure consistent, timely, and accurate data delivery across the organisation
Integrate diverse data sources and systems using scalable ingestion frameworks, defined patterns and APIs to unify enterprise data and reduce silos
Collaborate with data analysts, data scientists, AI engineers and data quality analysts through regular engagement, feedback sessions, and shared development environments to ensure the platform meets analytical and modelling needs effectively
Ensure data integrity, privacy, and compliance by implementing automated data quality checks, lineage
Document and maintain technical architecture, data flows, integration patterns and engineering standards using version-controlled repositories and collaborative tools to support maintainability, onboarding, and cross-functional transparency
WHO YOU ARE?
You have advanced knowledge of AWS, Databricks, and Apache Spark.
You have expertise in Medallion Architecture, having implemented Bronze, Silver, and Gold layers.
You adapt with confidence in a fast-paced, evolving environment.
You mentor business users, data professionals, and the data engineering team.
You deliver work using agile principles and collaboration tools such as GitHub, JIRA, Confluence, and Miro.