Job
Description
As a hands-on staff engineer at Addepar, your role will involve being at the forefront of building the modern data platform. You will work in partnership with engineering partners and other platform users to identify requirements and priorities, and map out solutions for challenging technology and workflow problems. Your responsibilities will include making Addepar's Data Lakehouse the central financial data hub by establishing integrations with various data sources. Additionally, you will act as a technical lead for a high-performing team of engineers in India, guiding them in designing, developing, and deploying data Lakehouse solutions with a focus on infrastructure and data tooling and integrations. Your contribution will also involve laying a solid foundation of the software architecture for the team in system design and code development. Qualifications Required: - Minimum 9+ years of relevant work experience in data platform development and management, with a strong foundation in data engineering, cloud infrastructure, and platform toolings for internal teams - Experience with Java or Python will be required - Practical knowledge of agile practices with an outlook that prioritizes experimentation and iteration combined with an ability to guide teams toward activities and processes that facilitate optimal outcomes - Experience with AWS will be highly preferred - Comfortable working in a cloud context, with automated infrastructure and service-oriented architecture - A product and customer-oriented mindset The engineering stack at Addepar includes PySpark on Databricks for data engineering, terraform for infrastructure, and streamlit for light-weight tooling apps. While experience in these technologies is preferred, there is flexibility to cross-train if coming from another similar context. Important Note: This role requires working from the Pune office 3 days a week in a hybrid work model. In addition to the core values, Addepar is proud to be an equal opportunity employer, promoting a welcoming environment where inclusion and belonging are held as a shared responsibility. The company commits to providing reasonable accommodation for individuals with disabilities during the job application or interview process and throughout employment. Please be cautious of phishing scams, as Addepar does not make job offers without a formal interview process and will not ask you to purchase equipment or supplies as part of your onboarding process. For any questions, reach out to TAinfo@addepar.com. As a hands-on staff engineer at Addepar, your role will involve being at the forefront of building the modern data platform. You will work in partnership with engineering partners and other platform users to identify requirements and priorities, and map out solutions for challenging technology and workflow problems. Your responsibilities will include making Addepar's Data Lakehouse the central financial data hub by establishing integrations with various data sources. Additionally, you will act as a technical lead for a high-performing team of engineers in India, guiding them in designing, developing, and deploying data Lakehouse solutions with a focus on infrastructure and data tooling and integrations. Your contribution will also involve laying a solid foundation of the software architecture for the team in system design and code development. Qualifications Required: - Minimum 9+ years of relevant work experience in data platform development and management, with a strong foundation in data engineering, cloud infrastructure, and platform toolings for internal teams - Experience with Java or Python will be required - Practical knowledge of agile practices with an outlook that prioritizes experimentation and iteration combined with an ability to guide teams toward activities and processes that facilitate optimal outcomes - Experience with AWS will be highly preferred - Comfortable working in a cloud context, with automated infrastructure and service-oriented architecture - A product and customer-oriented mindset The engineering stack at Addepar includes PySpark on Databricks for data engineering, terraform for infrastructure, and streamlit for light-weight tooling apps. While experience in these technologies is preferred, there is flexibility to cross-train if coming from another similar context. Important Note: This role requires working from the Pune office 3 days a week in a hybrid work model. In addition to the core values, Addepar is proud to be an equal opportunity employer, promoting a welcoming environment where inclusion and belonging are held as a shared responsibility. The company commits to providing reasonable accommodation for individuals with disabilities during the job application or interview process and throughout employment. Please be cautious of phishing scams, as Addepar does not make job offers without a formal interview process and will not ask you to purchase equipment or supplies as part
