Job Description

Are you a highly skilled Senior Data Engineer ready to lead and innovate in a dynamic, cloud-driven environment? We're looking for a pivotal team member to design, develop, and maintain cutting-edge data solutions, ensuring scalability, reliability, and top-tier performance. If you have a strong background in data engineering, a proven track record in leading technical teams, and thrive in an agile setting, we want to hear from you.



What You'll Be Doing:



Building and maintaining efficient ETL/ELT pipelines using tools like Apache Airflow and PySpark. Developing robust database schemas, dimensional models (Kimball/Inmon), and supporting data normalisation for both relational and NoSQL databases. Contributing to the development and maintenance of our data warehouses, data lakes, and data lakehouses. Working with diverse database systems, including Azure SQL, PostgreSQL, Google BigQuery, MongoDB, and Google Firestore. Handling structured, semi-structured, and big data file formats such as Avro, CSV, Parquet, ORC, and Delta. Developing and maintaining APIs for seamless data integration and workflows, with a solid understanding of REST and microservices architectures. Overseeing codebase maintenance and optimisation, leveraging Git for version control. Implementing thorough integration testing and ensuring high-quality deliverables for all new data processing scenarios. Providing technical design and coding assistance to team members, ensuring successful project milestones. Assessing and integrating new data sources to meet evolving business needs.




What We're Looking For:



Strong proficiency in Python and SQL (PostgreSQL or SQL Server preferred). Hands-on experience with Apache Airflow and PySpark. Familiarity with Databricks is essential Working knowledge of cloud platforms such as Azure, GCP, or AWS. Experience with data warehousing concepts, dimensional modelling, and database normalisation. Understanding of big data file formats like Avro, Parquet, ORC, and Delta. Proficiency in working with APIs, REST, and microservices architectures.




Education & Experience:



A Bachelor's degree in Computer Science, Data Science, or related fields. 5+ years of progressive experience in data engineering, cloud computing, and technology implementation. Experience managing multi-shore projects and working within cloud ecosystems (SaaS/PaaS). * Proven experience leading technical teams and mentoring team members.