Lead Data Engineer

As a Lead Engineer in the Epsilon Attribution/Forecasting Product Development team, you will play a key role in implementing and optimizing advanced data processing solutions using Scala, Spark, and Hadoop. You will collaborate with multi-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, as well as performing data integration and transformation tasks. You will troubleshoot issues, document processes, and communicate technical concepts clearly to both technical and non-technical partners. Additionally, you will focus on continuously enhancing our attribution and forecasting engines, ensuring they effectively meet evolving business needs.

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 8 years of strong experience in Scala programming and extensive use of Apache Spark for developing and maintaining scalable big data solutions on both on-premises and cloud environments, particularly AWS and GCP.
• Proficient in performance tuning of Spark jobs, optimizing resource usage, shuffling, partitioning, and caching for maximum efficiency.
• Skilled in implementing scalable, fault-tolerant data pipelines with comprehensive monitoring and alerting.
• Hands-on experience with Python for developing infrastructure modules.
• Deep understanding of the Hadoop ecosystem, including HDFS, YARN, and MapReduce.
• Proficient in writing efficient SQL queries for handling large volumes of data in various database systems.
• Experienced in building, scheduling, and maintaining DAG workflows.
• Familiar with data warehousing concepts and technologies.
• Capable of taking end-to-end ownership in defining, developing, and documenting software objectives and requirements in collaboration with stakeholders.
• 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 utilizing 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, prioritize tasks effectively, and perform under pressure.
• Experience in mentoring junior staff.

Advantageous to have experience in the below:

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

Skills

apache spark, hadoop, hdfs, mapreduce, scala, spark, yarn