Data Engineer

Responsibilities:

• Design, develop, and maintain robust ETL and data integration pipelines to ensure efficient data flow across systems.
• Build and manage data assets that support downstream teams such as data visualisation, data science, and MLOps.
• Identify and architect solutions requiring near real-time data processing to meet business and analytical needs.
• Translate business problems into scalable and well-defined data models and assets that drive decision-making.
• Collaborate with stakeholders across departments to gather requirements, ensure alignment, and deliver actionable insights.
• Integrate AI and automation into existing data workflows to enhance efficiency and innovation.
• Mentor and train new team members, fostering a culture of learning and continuous improvement within the data engineering team.

Requirements:

• Experience: 3+ years of hands-on experience as a data engineer or in a similar role.
• Proficiency in SQL and experience with data warehouses (e. g., Snowflake).
• Experience with big data processing frameworks like Apache Spark.
• Strong programming skills in Python, Scala, or Java.
• Experience with cloud platforms (AWS, Azure, or GCP) and familiarity with data services like AWS Glue, Redshift, or BigQuery.
• Knowledge of data architecture, data modelling, ETL processes, and data warehousing concepts.
• Familiarity with CI/CD pipelines and version control (e. g., Git).