Senior Data Engineer

The Product team forms the crux of our powerful platforms and helps connect millions of customers worldwide with the brands that matter most to them. This team of innovative problem solvers develops and builds products that position Epsilon as a differentiator, encouraging an open and balanced marketplace built on respect for individuals, where every brand interaction holds value. Our full-cycle product engineering and data teams chart the future and set new benchmarks for our products by using industry-standard methodologies and sophisticated capabilities in data, machine learning, and artificial intelligence. Driven by a passion for delivering smart end-to-end solutions, this team plays a key role in Epsilon's success story.

Responsibilities:

• As a Senior Data Engineer, you will be instrumental in implementing and optimising advanced data processing solutions using Scala, Spark, and Hadoop.
• You will collaborate with cross-functional teams to deploy scalable big data solutions on our on-premises and cloud infrastructure.
• Your responsibilities will include building, scheduling, and maintaining complex workflows, performing data integration and transformation tasks, and ensuring data quality through rigorous testing

Requirements:

• Strong written and verbal communication skills (in English) are required to facilitate work across multiple countries and time zones.
• Good understanding of Agile Methodologies - SCRUM.
• Over 5+ years in Scala programming and Apache Spark for developing scalable big data solutions on both on-premises and cloud platforms, such as AWS and GCP.
• Skilled in implementing scalable, fault-tolerant data pipelines with comprehensive monitoring and alerting systems.
• Implementing robust automated testing frameworks for big data jobs, ensuring comprehensive data integrity and performance validation.
• Use and implementation of tools such as Apache Airflow, Jenkins, or similar to automate complex testing workflows, including integration, regression, and performance testing.
• Conducting extensive data validation checks using automated and manual testing techniques to ensure accuracy and consistency in large-scale datasets.
• Deep understanding of the Hadoop ecosystem, including HDFS, YARN, and MapReduce.
• Hands-on experience with Python for infrastructure module development and strong SQL skills for handling large datasets.
• Familiar with data warehousing concepts and technologies.
• Experienced with GIT or equivalent source control systems.
• Proficient in developing and implementing unit test cases to ensure code quality and reliability and experienced in using integration testing frameworks to validate system interactions.
• Effective collaborator with stakeholders and teams to understand requirements and develop solutions.
• Ability to work within tight deadlines, prioritise tasks effectively, and perform under pressure.
• Experience in mentoring junior staff.

Advantageous to have experience on below:

• Hands-on with Databricks for unified data analytics, including Databricks Notebooks, Delta Lake, and Catalogues.
• Proficiency in using the ELK (Elasticsearch, Logstash, Kibana) stack for real-time search, log analysis, and visualisation.
• Strong background in analytics, including the ability to derive actionable insights from large datasets and support data-driven decision-making.
• Experience with data visualisation tools like Tableau, Power BI, or Grafana.
• Familiarity with Docker for containerization and Kubernetes for orchestration.

Skills

Apache Spark, HDFS, Hadoop, MapReduce, Scala, Spark, YARN