Key Facts

Remote From:

Romania , Europe

Category: Data Engineer

Full time

Senior (5-10 years)

English

Hard Skills

Scala (Programming Language) Apache Airflow Java (Programming Language) SQL (Programming Language) NoSQL Amazon Web Services gRPC Kubernetes Distributed Computing Pipeline Planning +4 more

Roles & Responsibilities

4+ years of experience in Data Engineering
2+ years of hands-on experience with Scala
2+ years of experience with SQL and NoSQL DBs
Hands-on experience with Spark and PySpark

Requirements:

Design and development of big data processing engine
Handle complex logic including geo-location analysis
Run processes across both cloud and on-prem environments
Work with ETL pipelines

Commit

About Commit

Commit is a global tech services company with offices in New York, Israel, 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 Software, IoT, Big Data, Cloud, 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.

Company type: SME

Founded: 2018

Company size: 501 - 1000

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Job description

Description

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