Data Engineering Leader — Analytics, AI & Data Ops

Corient Services LLC; Miami (FL); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

401(k) Plan with Employer Matching

Subsidized Medical Plan options

Employer paid Dental, Vision & Life Insurance

Training Reimbursement

Volunteer days

Job summary

Corient Services LLC in Miami, Florida, is seeking an experienced Data Engineering Team Leader to drive data projects and mentor engineers. The role involves establishing best practices for data pipelines and ensuring data integrity across all platforms.

The ideal candidate will have significant experience in data engineering, team leadership, and a background in financial services. A degree in a relevant field and proficiency in data engineering languages are also required.

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, analytics engineering, and data operations.

Responsibilities

• Lead, mentor, and develop a team of data engineers.
• Plan and manage delivery of data projects across multiple initiatives.
• Establish engineering best practices across data pipelines.
• Design and maintain robust data pipelines and workflows.
• Implement automated QA analytics and monitor data integrity.

Skills

Data engineering languages

SQL

Python

DBT

Analytical skills

Problem-solving

Communication

Documentation skills

Education

Degree in data, computer science or related discipline

Job description

Corient Services LLC in Miami, Florida, is seeking an experienced Data Engineering Team Leader to drive data projects and mentor engineers. The role involves establishing best practices for data pipelines and ensuring data integrity across all platforms.

The ideal candidate will have significant experience in data engineering, team leadership, and a background in financial services. A degree in a relevant field and proficiency in data engineering languages are also required.