We are looking for a Big Data / Data Engineer to join our growing team. In this role, you will be responsible for the design and development of our big data processing engine a heavy ETL pipeline handling complex logic including geo-location analysis, running across both cloud and on-prem environments.
Requirements:
- 4+ years of experience in Data Engineering
- 2+ years of hands-on experience with Scala (must) or Java (optional)
- 2+ years of experience with SQL and NoSQL DBs
- Hands-on experience with Spark & PySpark (must)
- Experience with Airflow (must)
- Experience with AWS and/or GCP
- Experience with Kubernetes (k8s) and on-prem deployments
- Solid understanding of distributed systems design, pipeline architecture, and partitioning strategies
- Deep understanding of Agile principles, practices and values
- Solid understanding of design patterns, software development techniques, and clean code practices
Advantage:
- Experience with Apache Iceberg, Helm Charts, or data catalog tools
- Experience with Spring Framework
- Experience with microservice architecture
- Experience working with DevOps and CI/CD practices
- Customer-facing experience or comfort working directly with clients
- Bachelor's, BSc or Master's degree in Computer Science or Engineering
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What We Do
Commit is a global tech services company with offices in Israel, US, Canada, UK, and Europe. The company was founded in 2005 and has over 700 multi-disciplinary innovation experts who serve a broad range of companies, from small startups to large enterprises in multiple business sectors. Commit specializes in advanced technologies and applications with dedicated practices in Cloud, GenAI, Software, IoT, Big Data, Cyber, Collaboration, Data center migration projects, and more. Commit offers innovative, end-to-end technology solutions by developing custom software and IoT platforms for clients looking to build their next-gen products within the modern ICT world. Commit’s complete and comprehensive engineering powerhouse of resources, and proprietary Flexible R&D methodology helps transform its clients’ technology visions into high-quality products while reducing costs and improving time-to-market.
