Data Engineer

Hays Specialist Recruitment LLC

United States

5 days ago

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Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

computerjobs.com

Tech stack

Agile Methodology Airflow Amazon Web Services Cloud Database Continuous Integration Information Engineering Data Infrastructure Extract Transform Load (ETL) Data Warehousing Python (Programming Language) Scrum Methodology Standard Sql

+5 more

Snowflake Gitlab Data Management Cloud Migration Data Pipelines

Job description

This is an opportunity to work on large-scale data engineering challenges, modernising Legacy environments and delivering robust, scalable data solutions that support critical business functions. You’ll collaborate with engineering, architecture and business teams to shape a modern analytics ecosystem and drive best practice across data engineering, automation and delivery. What You’ll Be Doing

Designing and building scalable ETL/ELT data pipelines
Developing cloud-native data solutions on AWS and Snowflake
Supporting the migration of Legacy data platforms to the cloud
Implementing data models and data warehousing solutions
Contributing to CI/CD, automation and engineering best practices
Working closely with stakeholders in an Agile environment

Requirements

Strong hands-on experience with Snowflake, AWS, Python and SQL
Proven background in Data Engineering and Data Warehousing
Experience with DBT and Airflow
Building and supporting enterprise-scale data pipelines
CI/CD experience, ideally using GitLab
Cloud migration and modern data platform implementation experience
Agile delivery experience (Scrum/Kanban)

Benefits & conditions

Opportunity to help build a modern cloud data platform at scale
Work with cutting-edge data engineering technologies
Strong technical environment with complex engineering challenges
Competitive day rate and flexible hybrid working
If you’re an experienced Data Engineer with a passion for the cloud, data platforms and modern engineering practices, we’d love to hear from you.