Our client, a rapidly growing wealth management and financial services firm, is seeking a Data Engineer to join its expanding data and analytics team. This role will be responsible for designing, building, and optimizing scalable data platforms that power enterprise reporting, analytics, and business intelligence. The ideal candidate has a strong technical foundation in modern data engineering practices and enjoys partnering with cross-functional teams to deliver reliable, high-quality data solutions in a fast-paced environment.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines, workflows, and data models to support enterprise analytics and reporting.
• Build and optimize ETL/ELT processes that ensure reliable, efficient, and timely delivery of business-critical data.
• Implement data engineering best practices across data modeling, quality, lineage, metadata management, documentation, and operational monitoring.
• Develop automated data quality validation, reconciliation, and monitoring processes to ensure data accuracy, completeness, and integrity.
• Support enterprise analytics initiatives by translating business requirements into scalable data solutions.
• Partner with Analytics, Operations, and business stakeholders to deliver data products that drive informed decision-making.
• Contribute to sprint planning, backlog prioritization, and execution across multiple concurrent data initiatives.
• Continuously identify opportunities to improve platform performance, scalability, and operational efficiency.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 6+ years of experience in data engineering, analytics engineering, or enterprise data platform development.
• Experience building enterprise data platforms supporting reporting, analytics, and business intelligence.
• Background in financial services, consulting, or high-growth technology environments is preferred.
• Strong understanding of modern data architecture, data modeling, and enterprise data management best practices.
• Excellent analytical, problem-solving, communication, and documentation skills.
• Ability to manage multiple priorities while collaborating effectively across technical and business teams.

Technical Skills

• Advanced proficiency with SQL, Python, and DBT.
• Experience designing and maintaining scalable ETL/ELT pipelines.
• Strong knowledge of data modeling, transformation frameworks, and enterprise data quality practices.
• Experience implementing automated monitoring, validation, and reconciliation processes.
• Familiarity with cloud-based data platforms and modern analytics ecosystems.
• Strong attention to detail and commitment to building reliable, production-quality data solutions.

Compensation & Schedule

• Full-time
• Hybrid schedule (4 days onsite)
• Location: Austin, TX or Miami, FL
• Compensation up to $160,000, depending on experience
• Interview process includes two virtual interviews followed by a final onsite interview.