Sr. Software Engineer - Analytics Platform

Location: New York, NY

Department: Data Architecture & Integration

The Role

Join Addepar’s innovative data and intelligence initiatives! We're seeking a Senior Software Engineer to craft and build a Data Analytics Platform, enabling our teams to make data driven decisions every day

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 $158,000 - $197,000 (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.

What You’ll Do

• Build and scale a comprehensive platform, formalizing and optimizing data analytics across teams
• Collaborate with product managers and engineers to understand requirements, and architect solutions for sophisticated data and workflow challenges
• Use core Addepar systems like the Data Lakehouse to advise and strategize Ops and Data Governance infrastructure
• Simplify processes by promoting strategic data architecture and optimized workflows

Who You Are

• 5+ years of relevant work experience that shows proficiency in platform development, particularly in enabling data engineering outcomes
• Must have strong experience with Java or Python
• Proficient in one or more cloud platforms (AWS, GCP, Azure), with hands-on experience in cloud infrastructure and handling data analytics workloads
• Strong expertise in CI/CD for data engineering pipelines—building, automating, and optimizing the pipeline lifecycle
• Skilled in monitoring and observability tools like FiddlerAI, Datadog, and Grafana to track system performance, and system health
• Knowledge of Infrastructure as Code tools (Terraform, Ansible, CloudFormation) for consistent, scalable environment setups
• A collaborative, low-ego problem-solver who takes ownership and delivers results
• [Bonus] Experience in handling large-scale datasets and high velocity data streams
• [Bonus] Familiarity with the financial domain
• [Bonus] PySpark and Databricks experience (or similar technologies with a willingness to cross-train)