01Overview
About the roleWe are looking for a Data Engineer to join a clientfocused engagement, splitting time evenly between production support and new development. The role combines daytoday pipeline maintenance with the design and optimisation of scalable data solutions.Key responsibilitiesProvide 50% of your time supporting existing data pipelines, monitoring, troubleshooting and resolving incidents.Design, build and maintain the remaining 50% of scalable ETL/ELT workflows using Python, SQL and Spark.Collaborate with crossfunctional and client teams to translate data requirements into technical solutions.Perform rootcause analysis on pipeline failures and implement fixes with minimal downtime.Optimise data workflows for performance, reliability and costefficiency.Document architecture, processes and support runbooks for knowledge continuity.Participate in oncall rotations and support the client environment as needed.Work with Databricks and/or AWS cloud services to build or support data solutions.Required profile24 years of handson experience in a Data Engineering role.Strong proficiency in Python and SQL.Practical experience with Apache Spark.Prior experience on clientbased projects (mandatory).Ability to balance operational support with development tasks.Excellent problemsolving and communication skills for clientfacing situations.Required skillsPythonSQLApache SparkDatabricks (preferred)AWS services such as S3, Glue, EMR, Lambda, Redshift (preferred)CI/CD pipelines for data engineering (preferred)Workflow orchestration tools like Airflow (preferred)What we offerCompetitive salary and a strong insurance package.Extensive learning and development resources to support career growth. .
