Offer summary

Qualifications:

Minimum 5 years of experience as a Data Engineer., Proficiency in Python for data pipelines and ETL processes., Strong SQL skills and experience designing cloud-based data warehouses like Redshift, Snowflake, or BigQuery., Knowledge of AI/ML tools such as SageMaker, Vertex AI, or BigQuery ML..

Key responsibilities:

Design and develop data solutions for clients and projects.

Build data pipelines, data lakes, and data warehouses using advanced tools.

Create dashboards and reports to visualize data insights.

Collaborate with teams to understand needs and define data interfaces.

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.

Job description

Description

Commit Data is looking for a highly skilled Data Engineer to join our growing Data Analytics Department.

As a Data Engineer in a multi cloud company, you will build data-driven solutions for our customers using cutting-edge data tools and large-scale data on AWS\GCP\Azure.

Job Responsibilities:

Lead data solutions design and development for our various clients and projects.
Design the solution by understanding the needs, modeling the data, choosing the right tools and defining the interfaces/dashboards.
Develop Data Pipelines, Data Lakes, DWHs, AI\ML models, Dashboards and reports using advanced tools and leading technologies.

Requirements

Requirements:

5+ years of relevant experience as Data Engineer – a must.
Experience with Python based data pipelines/ETLs and other ETL\ELT tools (such as Glue, Rivery, Data Factory, DBT).
High Proficiency in SQL – a must.
Experience designing and developing DWHs in the cloud – Redshift\Snowflake\BigQuery is a must.
Experience with BI & visualizations tools like Tableau\Quicksight\Power BI\Looker.
Knowledge and experience with AI\ML (working with tools like SageMaker\ Bedrock\ Q\ BigQuery ML\ Vertex AI\ Gemini) - big advantage.
Strong analytical and problem-solving skills with attention to details.
High self-learning skills
Fluent English