Design and build resilient and efficient data pipelines, develop end-to-end data solutions, and maintain existing pipelines for better scalability, adaptability, and maintainability. Collaborate with data scientists, analysts, product managers, and various engineering teams to optimize product and service performance through data.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
- 4+ years of hands-on experience working primarily with data in roles such as Data Engineer, Data Analyst, or Data Scientist
- Proficient in SQL, data modeling, ETL pipeline development, and at least one programming language (e.g., Python, Java, Go, or Scala)
- Strong experience with distributed data processing frameworks such as Spark or Flink
- Familiarity with orchestration frameworks
- Experience with distributed OLAP datastores such as Druid or ClickHouse
- Hands-on experience with ELK stack (Elasticsearch, Logstash, Kibana) for log aggregation, analysis