Senior Software Engineer (Analytics Platform)

• 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
• 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

Benefits

• Equity: Stretch the idea of ownership beyond your day-to-day and take pride in being an owner in the growth of Addepar
• Global Hybrid Workforce: Whether you work remotely or on-site, you’ll have the opportunity to build and collaborate with colleagues around the world
• Flexible Time Off: Spend time traveling, celebrating with friends and family or relax on your schedule
• Benefits Packages: Competitive medical, dental and vision benefits along with a monthly wellness allowance to keep you healthy and happy
• Learning & Development Allowance: Your continued growth and development are important to us
• Dynamic Team: Strong investment in the best talent at the intersection of technology and finance

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