Blue Bridge People

Blue Bridge People is a talent partner that connects top technical and business professionals with forward-thinking organizations. Since 2020, they have focused on humanizing the hiring experience and building strong relationships to deliver world-class STEM talent in IT, Engineering, ERP, Data Engineering, AI, and Modernization technologies. Their approach combines US-based recruiting excellence with cost-effective global partnerships across Asia, India, China, and EMEA regions. They aim to bridge the gap between innovative companies and exceptional talent, offering solutions for contract, permanent placements, and executive hiring. Blue Bridge People has supported over 100,000+ candidates and serves Fortune 1000 companies, focusing on solving talent pipeline challenges through tailored solutions that drive business forward.

AIEngineeringGlobal WorkforceITRecruitingSTEM TalentTalent AcquisitionWorkforce Solutionsbluebridgepeople.com

Blue Bridge People

AIEngineeringGlobal WorkforceITRecruitingSTEM TalentTalent AcquisitionWorkforce Solutionsbluebridgepeople.com

HQCincinnati, US

Team Size19

Open Jobs41

Total Funding-

Latest FundraiseUnknown

Join the Team

Data Engineer + Tester

RemoteMX

Remote • MX

Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.

Mobile Developer

Part-timeRotterdam, NL

Part-time • Rotterdam, NL

Product Designer

InternshipSan Francisco, US

Internship • San Francisco, US

Technical Writer

InternshipHamburg, DE

Internship • Hamburg, DE

DevOps Engineer

Full-timeJerusalem

Full-time • Jerusalem

Machine Learning Engineer

Full-timeRotterdam, NL

Full-time • Rotterdam, NL

Technical Writer

ContractAustin, US

Contract • Austin, US

This is a 100% REMOTE contract role. My client is looking for a near-shore resource who can work on EST.

**Please, no C2C companies **

Job Title: Senior Data Engineer (Data Platform & Quality)

Overview

We are seeking a Senior Data Engineer with strong testing expertise to support and evolve a modern, cloud-based data platform. This role will focus on building and maintaining high-quality data ingestion pipelines, enabling Data-as-a-Service capabilities, and enforcing data quality and reliability across the platform. The ideal candidate brings hands-on engineering skills, testing discipline, and the ability to lead technical initiatives within a growing data ecosystem.

Key Responsibilities

Design, build, and maintain scalable data ingestion and processing pipelines using AWS-native services.
Develop and manage data workflows leveraging YAML-based configurations.
Ensure data quality, validation, and reliability across the data platform.
Support and enhance a Data-as-a-Service architecture consumed by downstream applications and analytics teams.
Implement and maintain ETL workflows using AWS Glue and related services.
Work with cloud-based storage and formats, including S3 buckets and Parquet files.
Partner with platform, analytics, and application teams to support evolving data needs.
Lead technical efforts, mentor junior engineers, and contribute to architectural decisions.
Monitor and improve system performance, observability, and reliability using tools such as Datadog.
Contribute to platform expansion initiatives, including future adoption of Databricks.

Required Qualifications

Strong experience as a Data Engineer working on production-grade data platforms.
Proficiency in Python for data engineering and automation.
Hands-on experience with AWS cloud-based architectures, including:
S3
Parquet file formats
AWS Glue-based ETL workflows
Solid understanding of data quality frameworks, testing strategies, and validation practices.
Testing expertise using tools such as Selenium, Cucumber, and Postman.

Nice-to-Have Qualifications

Experience with Databricks or interest in expanding the platform into Databricks-based solutions.
Knowledge of Cypress for test automation.
Strong SQL skills for data analysis and validation.
Experience with CI/CD pipelines and automated testing in data environments.
Familiarity with synthetic data generation techniques.