Data Engineer

SUMMARY:
Ready to build data magic that powers real business impact?
If you love transforming raw information into reliable, scalable, high-performance data systems — this one’s for you!

We’re looking for a talented Data Engineer who enjoys crafting solid data architecture, optimising databases, and making sure data flows effortlessly from source to solution. This role blends hands-on database administration with modern data engineering, giving you the chance to work closely with analysts and developers to create high-quality pipelines, dependable datasets, and innovative data products.

POSITION INFO:

What You’ll Be Doing

• Creating large, complex data sets that meet both functional and non-functional business requirements
• Designing, developing, and maintaining scalable ETL pipelines and data workflows
• Building reliable infrastructure to extract, transform, and load data from diverse sources — often Cloud-based
• Identifying opportunities to automate, optimise, and improve internal data processes
• Developing tools and solutions that turn data into actionable business insights
• Ensuring data quality, consistency, integrity, and security across environments
• Driving best practices in data engineering, performance, and documentation

Skills & Experience You Bring

• Bachelor’s Degree in Computer Science, Engineering, Mathematics, or similar
• 5–7 years’ experience in data engineering, database management, or a related role
• Strong programming capability in Python or Scala
• Advanced SQL skills and experience with relational databases (MSSQL, MySQL, PostgreSQL, etc.)
• Exposure to NoSQL technologies
• Proven experience in performance tuning and database optimisation
• Solid understanding of data integration concepts and practices
• Exposure to BI tools (Power BI, Yellowfin, etc.)
• Experience with MS SQL Replication and data archiving strategies is beneficial
• Experience with cloud technologies (AWS, Azure, GCP) and tools like S3, Lambda, Redshift, BigQuery, or Snowflake
• Familiarity with big-data ecosystems such as Apache Spark, Databricks, or Hive
• Understanding of data modelling, warehousing concepts, and data governance
• Exposure to data cleansing and de-duplication strategies

Bonus Points For

• Experience with streaming platforms (Kafka, Spark Streaming, Flink)
• Knowledge of Docker and Kubernetes
• Understanding of CI/CD and infrastructure-as-code
• Exposure to machine learning workflows or MLOps