Data Engineer (Remote - US) - job 1 of 6

This position is posted by Jobgether on behalf of Harvard Business Publishing. We are currently looking for a Data Engineer in United States.

This role offers a unique opportunity to design, build, and maintain robust data infrastructure that supports large-scale data processing and analysis across multiple business functions. As a central member of the data engineering team, you will work closely with product engineers, data scientists, and AI developers to deliver scalable data pipelines and models that drive key business insights and power user-facing applications. This position requires a balance of hands-on engineering, strategic architectural thinking, and cross-functional collaboration in a mission-driven environment focused on innovative management education.

Accountabilities

• Lead the entire data engineering lifecycle including requirements gathering, technical design, development, deployment, and production support.
• Design, develop, and maintain scalable, secure, and high-performance ELT/ETL pipelines and data warehouses.
• Collaborate with analytics, data science, and business teams to create and evolve data models for dashboards, AI/ML projects, and SaaS products.
• Produce clear technical documentation such as system diagrams, data flow charts, and runbooks to facilitate decision-making and maintenance.
• Evaluate design trade-offs balancing cost, performance, flexibility, and supportability, ensuring alignment with IT strategy and scalability goals.
• Ensure smooth project transitions to operations with comprehensive documentation and knowledge transfer.

• Minimum 5 years of experience in data engineering or related fields delivering production-grade data pipelines and platforms.
• Expertise in designing, building, and operating high-volume ELT/ETL data pipelines from diverse sources.
• Strong SQL skills, particularly in Snowflake SQL with experience in complex analytics and DBT standards.
• Proficient in developing modular dbt models, implementing tests, documentation, and enforcing coding standards via CI/CD.
• Hands-on experience with data modeling and maintaining data warehouses on cloud platforms such as Snowflake.
• Experience with data quality frameworks ensuring accuracy, consistency, and lineage.
• Excellent communication and stakeholder management skills to translate business needs into technical solutions.
• Analytical mindset with ability to assess trade-offs and recommend optimal data architectures.
• Proven ability to monitor pipelines, diagnose issues, and provide production support with root-cause analysis.
• Proficiency in Python programming.

Preferred:

• Experience with Snowflake Snowpark Container Services for ML model development and deployment.
• Familiarity with AWS services such as S3, IAM, Lambda for data lake integration and automation.
• Knowledge of ML Ops processes for model deployment and support in Snowflake and AWS environments.

• Competitive salary range of $140,000 - $150,000 with eligibility for performance-based variable pay.
• Inclusive culture fostering trust, engagement, and a sense of belonging.
• Programs supporting career development and employee wellness including education reimbursement and early-release Summer Fridays.
• Comprehensive benefits package with a focus on work-life balance.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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