Data Engineering Manager at Blend360

St. Louis, Missouri, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Aug, 26

Salary

75.0

Posted On

22 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Engineering Management, Technical Delivery Leadership, Agile Methodologies, Distributed Team Management, Code Review, Engineering Governance, Data Engineering, Cloud Data Platforms, AI-Assisted Development, Stakeholder Management, Python, SQL, Spark, AWS, CI/CD, DevOps

Industry

Professional Services

Description

Company Description BLEND360 is an acclaimed, forward-thinking Data, Digital Marketing, & AI Solutions Company, dedicated to fueling remarkable outcomes for our Fortune 500 clients. Our trajectory is one of continuous expansion, emerging at the crossroads of cutting-edge analytics, data proficiency, technology, and digital marketing excellence. Job Description This is an hourly/contract opportunity that could become permanent over time. We are seeking a Data Engineering Manager to lead execution delivery for a large-scale Marketing Data Layer initiative supporting a major telecommunications customer. This role will oversee a 16-person nearshore engineering organization responsible for building and scaling enterprise data ingestion and transformation capabilities within a modern AWS-based ecosystem. The ideal candidate combines strong engineering leadership with deep delivery management experience in distributed data engineering environments. This role requires someone who can drive execution excellence, establish engineering rigor, and lead teams through modern AI-assisted development practices while maintaining high standards for quality, velocity, and operational reliability. What You’ll Do Own day-to-day leadership and operational management of a 16-person nearshore Data Engineering execution pod Drive delivery accountability across engineering squads, ensuring high-quality, scalable, and reliable implementations Manage sprint planning, execution, and delivery coordination across distributed nearshore teams Lead daily standups and establish strong communication rhythms that effectively bridge timezone and cross-functional collaboration gaps Conduct code reviews and enforce engineering best practices, development standards, and quality controls Oversee onboarding, ramp-up, and ongoing enablement of nearshore contractors and engineering resources Establish and manage AI-assisted development governance, including: Prompt engineering patterns and usage standards Review processes for AI-generated code Productivity measurement and engineering adoption practices Track and improve engineering delivery metrics, including: Pull request cycle time Deployment frequency Pipeline reliability Test coverage Delivery throughput and quality Partner closely with architects, product stakeholders, and client leadership to ensure successful execution against business priorities Foster a culture of accountability, collaboration, continuous improvement, and engineering excellence Qualifications Required Skills Strong engineering management and technical delivery leadership experience Deep understanding of Agile delivery methodologies and sprint execution management Experience leading distributed, nearshore, or offshore engineering teams Strong code review and engineering governance capabilities Hands-on background in modern data engineering and cloud data platforms Experience managing engineering performance metrics and operational KPIs Familiarity with AI-assisted software development workflows and governance practices Strong communication and stakeholder management skills in client-facing environments Technical Background Experience with modern data engineering frameworks and cloud ecosystems Strong understanding of ETL/ELT pipelines, orchestration, and large-scale data processing Familiarity with technologies such as: Python SQL Spark / PySpark Cloud data platforms (AWS preferred) CI/CD and DevOps engineering practices Understanding of enterprise data platform delivery and operational reliability best practices Required Experience 7+ years of experience in data engineering or related engineering disciplines 3+ years managing engineering teams of 10+ resources Proven experience leading distributed engineering organizations in fast-paced delivery environments Experience managing enterprise-scale data initiatives and cross-functional delivery programs Consulting or client-facing delivery experience strongly preferred What Makes You Successful You lead with accountability, clarity, and operational discipline You are highly organized and execution-focused while maintaining strong technical credibility You know how to scale engineering teams and improve delivery performance in complex enterprise environments You balance speed and quality while creating sustainable engineering practices You are passionate about mentoring engineers, improving team effectiveness, and driving continuous improvement Additional Information #LI-AJ1 The starting pay range for this role is $65 - $75/hr. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. It is not typical for an individual to be hired at or near the top of the range and determining factors for compensation are considered for each individual circumstance. BLEND360 offers a competitive benefits program designed to support the health and financial well-being of our team members and their families. Benefits vary by role and eligibility and may include medical, dental, and vision coverage, a 401(k) plan, paid time off, paid holidays, commuter benefits, flexible spending accounts, life and disability insurance, and employee assistance programs. Compensation: USD 65 - USD 75 - hourly

Responsibilities

Lead a 16-person nearshore engineering team to build and scale enterprise data ingestion and transformation capabilities for a major telecommunications client. Oversee sprint planning, AI-assisted development governance, and ensure high-quality delivery within an AWS ecosystem.