Data Engineer – Build Scalable Data Pipelines

About the role

We are looking for a Data Engineer to design, build, and optimise scalable data solutions that power analytics, reporting and business intelligence. You will create robust data pipelines, integrate multiple data sources and ensure high‑quality, governance‑compliant datasets on modern cloud platforms.

Key responsibilities

• Design, develop and maintain ETL/ELT pipelines and workflows.
• Build data ingestion solutions from ERP systems, APIs, databases and external sources.
• Develop and support data warehouse and lakehouse architectures for analytics.
• Implement batch and real‑time processing using tools such as Apache Spark.
• Monitor, troubleshoot and optimise pipelines for performance, scalability and cost.
• Ensure data quality, lineage, security and compliance.
• Automate workflows and implement CI/CD practices.
• Collaborate with analysts, BI teams and IT to deliver data requirements.
• Maintain technical documentation for pipelines and data models.

Required profile

• Bachelor’s degree in Computer Science, IT, Data Science or related field.
• 3–7 years of experience in data engineering or a similar role.
• Strong proficiency in SQL and Python for data transformation.
• Hands‑on experience with Apache Spark (PySpark preferred).
• Experience with cloud platforms such as Azure, AWS, Google Cloud, Databricks or Microsoft Fabric.
• Solid understanding of data warehousing, lakehouse architecture and data governance.
• Experience integrating data from ERP systems, APIs and relational databases.
• Familiarity with CI/CD pipelines and automated data workflows.

Required skills

• SQL
• Python
• Apache Spark / PySpark
• Azure
• AWS
• Google Cloud
• Databricks
• Microsoft Fabric
• CI/CD