Data Engineering Manager

Corient; United States; On-site; USD 130,000 - 160,000; Full time

Job summary

Corient is seeking an experienced Data Engineering Lead who will lead and mentor a team of data engineers for critical data projects. The role requires strong expertise in data engineering processes and tools. The ideal candidate has 8-12+ years of relevant experience and a solid background in financial services or technology. Responsibilities include overseeing data operations and establishing best practices. Effective communication and problem-solving skills are essential. This position is based in the United States.

Qualifications

• 8-12+ years of experience in data engineering, data platform development, or analytics engineering.
• 3-5+ years of experience leading engineering teams.
• Background in Financial Services, consulting, or high-growth technology environments preferred.
• Proven experience building enterprise data platforms supporting reporting and analytics.
• Hands-on experience with data modeling, ETL/ELT pipelines, and analytics engineering.

Responsibilities

• Lead, mentor, and develop a team of data engineers.
• Establish engineering best practices across data operations.
• Design, architect, develop, and maintain scalable data pipelines.
• Implement automated QA analytics to ensure data integrity.
• Support cross-functional teams in delivering data solutions.

Skills

Data engineering

Leadership

Data modeling

SQL

Python

Data operations

Analytical skills

Problem-solving

Communication

Attention to detail

Education

Degree in data, computer science, or related discipline

Tools

ETL/ELT tools

DBT

Job description

Join a team that values your ambition and empowers your growth.

Key Responsibilities

• Data Engineering team leadership. Lead, mentor, and develop a team of data engineers supporting reporting, analytics, data science, AI, and data quality initiatives. Plan and manage delivery of data projects across multiple concurrent data initiatives
• Technical data operations and execution. Establish engineering best practices across data pipelines, modeling, data quality, lineage, metadata management, documentation and operational monitoring. Oversee sprint planning, backlog prioritization, and execution across multiple data initiatives.
• Enterprise Data Layer operation. Design, architect, develop, and maintain robust and scalable data pipelines, transformations, models, and workflows. Develop and operate automated data jobs for data science, analytics, and reporting purposes.
• Data QA operations. Implement automated QA analytics, reconciliations, and monitoring to ensure data integrity across enterprise platforms and enterprise data layer. Establish data quality frameworks including validation, monitoring, reconciliation, and alerting, ensuring strong governance around data accuracy, completeness, and timeliness across critical datasets.
• Cross-functional data engineering support. Support Analytics, Operations, and Business teams in data initiatives, deeply understanding functional requirements and delivering data solutions that meet these needs in a timely and reliable fashion.

Qualifications

• 8-12+ years of experience in data engineering, data platform development, or analytics engineering.
• 3-5+ years of experience leading engineering teams.
• Background in Financial Services, consulting, or high‑growth technology environments preferred.
• Distinguished academic track record in data, computer science, or related discipline.
• Proven experience building enterprise data platforms supporting reporting and analytics.
• Hands‑on experience with data modeling, ETL/ELT pipelines, analytics engineering, and data operations.
• Proficiency in data engineering languages, frameworks, and tooling, including SQL, Python, and DBT.
• Strong analytical, problem‑solving, and critical thinking skills.
• Effective communication, both orally and in writing.
• Strong documentation and attention to detail.