Data Engineering Lead

This is a Fully Remote Job
About Our Client:
The organization operates in the data and machine learning engineering space, focusing on delivering enterprise data products that support business decision making. It addresses challenges related to data reliability, scalability, and quality by establishing technical standards and engineering practices across distributed teams and external partners.
About the Opportunity:
The DATA ENGINEERING LEAD is responsible for providing senior technical leadership within the data and ML engineering function. This role sets technical standards, oversees design and delivery of data pipelines and analytics-ready models, and ensures data products meet quality and scalability requirements. The position drives engineering excellence, coaches teams, and aligns data solutions with business needs and enterprise architecture.
Responsibilities:
Provide technical leadership for data engineering design, build quality, and delivery standards.
Review designs and enforce coding standards for internal and partner teams.
Own engineering standards for model design, code review, CI/CD, testing, documentation, and deployment.
Lead design and delivery of analytics-ready data models and transformations using dbt.
Build and operate cloud-native data pipelines on AWS focusing on reliability and cost efficiency.
Develop reusable data engineering patterns for ingestion, transformation, and delivery.
Provide technical direction to distributed engineering teams and external partners.
Coach and develop data and analytics engineers through design reviews and knowledge transfer.
Document engineering patterns and runbooks to retain critical knowledge.
Drive data quality practices including monitoring, testing, and lineage.
Lead root cause analysis and remediation of complex production data issues.
Translate stakeholder business needs into scalable data engineering designs.
Collaborate with data architecture, cloud engineering, and security teams to ensure compliance.
Requirements:
Bachelor’s degree in Computer Science, Computer Engineering, or related field; Master’s preferred.
8–10 years of experience building enterprise data platforms and analytics-ready models.
3+ years of technical leadership in data engineering, including design review and standards enforcement.
Hands-on experience with dbt for transformations, testing, documentation, and CI/CD.
Experience delivering data pipelines on AWS and cloud data warehouses.
Skilled in providing technical direction to distributed teams and external partners.
Knowledge of data quality practices such as automated testing, reconciliation, and monitoring.
Preferred experience supporting machine learning and advanced analytics datasets.
Expertise in dimensional modeling, dbt best practices, and SQL performance tuning.
Proficiency with SQL, Python, and orchestration tools like Airflow.
Familiarity with AI-assisted development workflows for pipeline development.
Strong problem-solving, communication, and stakeholder engagement skills.
Ability to work effectively in fast-paced, matrixed, global environments.
Pay Range and Compensation Package:
The pay range and compensation package for this role will be determined based on the candidate's experience, skills, and other relevant factors.
Benefits & Perks:
Medical insurance
Dental insurance
401(k)
Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.
Note:
TalentHop is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.

Work arrangement
Yes