Job Description

Our client, a rapidly growing wealth management and financial services firm, is seeking a Data Engineering Manager to lead the development and evolution of its enterprise data platform. This is a highly technical leadership role best suited for a hands-on engineering leader who enjoys mentoring teams while remaining deeply involved in architecture, coding, and solution design. The ideal candidate will bring extensive Python expertise, a strong background in modern data engineering, and experience building scalable data platforms that support analytics, reporting, and AI initiatives.

Key Responsibilities

• Lead, mentor, and develop a team of Data Engineers supporting enterprise reporting, analytics, AI, and data science initiatives.
• Design, build, and maintain scalable data pipelines, workflows, data models, and enterprise data architecture.
• Establish engineering best practices for ETL/ELT development, data quality, lineage, metadata management, documentation, and operational monitoring.
• Drive sprint planning, backlog prioritization, and technical execution across multiple concurrent projects.
• Develop automated data quality frameworks, validation processes, monitoring, reconciliation, and alerting to ensure data accuracy and reliability.
• Partner closely with Analytics, Operations, and business stakeholders to translate business requirements into scalable data solutions.
• Identify opportunities to improve platform performance, scalability, automation, and operational efficiency.
• Provide technical leadership through architecture reviews, code reviews, and engineering best practices while remaining an active contributor to development efforts.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
• 8–12+ years of experience in data engineering, analytics engineering, or enterprise data platform development.
• 3–5+ years of experience leading engineering teams or serving as a technical lead.
• Experience building enterprise data platforms supporting analytics, reporting, and business intelligence.
• Background in financial services, consulting, or high-growth technology organizations is preferred.
• Excellent leadership, communication, problem-solving, and stakeholder management skills.

Technical Skills

• Expert-level proficiency in Python (required); this role is highly hands-on and requires deep technical expertise.
• Advanced experience with SQL and DBT.
• Strong expertise designing and maintaining scalable ETL/ELT pipelines and modern data architectures.
• Deep understanding of data modeling, transformation frameworks, metadata management, and enterprise data quality practices.
• Experience implementing automated monitoring, validation, reconciliation, and operational tooling.
• Familiarity with cloud-based data platforms and modern analytics ecosystems.

Compensation & Schedule

• Full-time
• Hybrid schedule (4 days onsite)
• Location: Austin, TX or Miami, FL
• Compensation up to $200,000, depending on experience
• Interview process includes two virtual interviews followed by a final onsite interview.