- 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
Proficient in one or more cloud platforms (AWS, GCP, Azure), with hands-on experience in cloud infrastructure and handling data analytics workloads5+ years of relevant work experience that shows proficiency in platform development, particularly in enabling data engineering outcomesKnowledge of Infrastructure as Code tools (Terraform, Ansible, CloudFormation) for consistent, scalable environment setupsSkilled in monitoring and observability tools like FiddlerAI, Datadog, and Grafana to track system performance, and system healthMust have strong experience with Java or Python(Bonus) Familiarity with the financial domain(Bonus) Experience in handling large-scale datasets and high velocity data streamsStrong expertise in CI/CD for data engineering pipelines-building, automating, and optimizing the pipeline lifecycleA collaborative, low-ego problem-solver who takes ownership and delivers results(Bonus) PySpark and Databricks experience (or similar technologies with a willingness to cross-train)
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