Build and scale Addepar's Analytics Platform using the Data Lakehouse to optimize data analytics, workflows, Ops, and Data Governance. Requires 5+ years experience in platform development for data engineering outcomes, strong Java/Python skills, cloud platforms, CI/CD pipelines, IaC, and observability tools.
Salary not listed
On-site5+ YOEData Engineering
About the role
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)
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