The Role\n\nPortfolio Data Integration is part of the broader Addepar Platform team. The overall Addepar Platform provides a single source of truth โdata fabricโ used by the Addepar product set, including a centralized and self-describing repository (a.k.a Data Lake), a set of API-driven data services, an integration pipeline, analytics infrastructure, warehousing solutions, and operating tools. The team has responsibility for all data acquisition, conversion, cleansing, disambiguation, modeling, tooling and infrastructure related to the integration of client portfolio data.\n\nAddeparโs core business relies on the ability to quickly and accurately ingest data from a variety of sources, including 3rd party data providers, custodial banks, data APIs, and even direct user input. Portfolio Data integrations and feeds are a highly critical cross-section of this set, allowing our users to get automatically updated and reconciled information on their latest holdings onto the platform.\n\nAs a data engineer for this team, you will execute the development of new data integrations and maintenance of existing processes in order to expand and improve our data platform. Youโll be adding automation and functionality to our distributed data pipelines by writing PySpark code and integrating it within our Databricks Data Lake. As you gain more experience, youโll contribute to increasingly challenging engineering projects within our platform with the ultimate goal of dramatically increasing the throughput of data ingestion for Addepar. This is a crucial, highly visible role within the company. Your team is a big component of growing and serving Addeparโs client base with minimal manual effort required from our clients or from our internal data operations team.\nWhat Youโll Do\n\n\n* Complete individual project priorities, deadlines, and solutions.\n\n* Build pipelines that support the ingestion, analysis, and enrichment of financial data in partnership with business data analysts\n\n* Improve the existing pipeline to increase the throughput and accuracy of data\n\n* Develop and maintain efficient process controls and accurate metrics to ensure quality standards and organizational expectations are met\n\n* Partner with members of Product and Engineering to design, test, and implement new processes and tooling features that improve data quality as well as increase operational efficiency\n\n* Identify areas of automation opportunities and implement improvements\n\n* Understand data models and schemas, and work with other engineering teams to recommend extensions and changes\n\n\n\nWho You Are \n\n\n* A computer science degree or equivalent experience\n\n* 2-6 years of professional software engineering experience\n\n* Competency with relevant programming languages (Java, Python)\n\n* Familiarity with relational databases and data pipelines\n\n* Experience or interest in data modeling, visualization, and ETL pipelines\n\n* Knowledge of financial concepts (e.g., stocks, bonds, etc.) is encouraged but not necessary\n\n* Passion for the finance and technology space and solving previously intractable problems at the heart of investment management\n\n\n \n\n#Salary and compensation\n
No salary data published by company so we estimated salary based on similar jobs related to Finance and Engineer jobs that are similar:\n\n
$45,000 — $85,000/year\n
\n\n#Benefits\n
๐ฐ 401(k)\n\n๐ Distributed team\n\nโฐ Async\n\n๐ค Vision insurance\n\n๐ฆท Dental insurance\n\n๐ Medical insurance\n\n๐ Unlimited vacation\n\n๐ Paid time off\n\n๐ 4 day workweek\n\n๐ฐ 401k matching\n\n๐ Company retreats\n\n๐ฌ Coworking budget\n\n๐ Learning budget\n\n๐ช Free gym membership\n\n๐ง Mental wellness budget\n\n๐ฅ Home office budget\n\n๐ฅง Pay in crypto\n\n๐ฅธ Pseudonymous\n\n๐ฐ Profit sharing\n\n๐ฐ Equity compensation\n\nโฌ๏ธ No whiteboard interview\n\n๐ No monitoring system\n\n๐ซ No politics at work\n\n๐ We hire old (and young)\n\n
\n\n#Location\nPune, Maharashtra, India
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