Software Engineering Manager, Data Intelligence

Addepar•New York, NY

7d•$160,000 - $250,000

About The Position

Addepar is hiring a hands-on engineering manager who will bring to bear their expertise, leadership, and platform management skills to create solutions for Financial Data Lakehouse, AI, and Data Governance. Addepar takes a market-based approach to pay. A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The range displayed on each job posting reflects the minimum and maximum target base salary for roles in Colorado, California, and New York. The current range for this role is $160,000 - $250,000 (base salary) + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additionally, these ranges reflect the base salary only, and do not include bonus, equity, or benefits. Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.

Requirements

8+ years of relevant experience in data platform development, including at least 2+ years of formal people management or successful team leadership experience
Highly proficient in Python and data engineering, with the ability to "lead from the trenches" and solve deep technical hurdles alongside your team
Practical experience building and maintaining robust data pipelines and service-oriented architectures within a cloud environment (AWS preferred)
Strong advocate for agile methodologies, prioritizing iterative development, experimentation, and continuous process improvement to optimize team velocity
Exceptional at bridging the gap between technical details and business outcomes, with the ability to manage stakeholder expectations across different regions

Nice To Haves

Familiarity with PySpark and Databricks is a significant plus; you should be comfortable guiding a team through large-scale data processing challenges

Responsibilities

Direct Team Leadership: Build, lead, and develop a high-performing team of engineers, fostering a culture of accountability, growth, and technical excellence
Execution & Delivery: Work in partnership with global product managers and technical partners to translate business requirements into actionable technical roadmaps, ensuring predictable delivery of complex data workflows
Hands-on Technical Contribution: Drive the team’s output by staying active in the codebase—writing production code, performing deep code reviews, and designing scalable integrations for the Data Lakehouse
Cross-Coast Collaboration: Coordinate effectively with distributed teams across time zones to ensure alignment on global priorities and seamless technical integration
Mentorship: Actively coach and mentor junior and senior engineers, helping them navigate technical challenges and advance their professional careers