Juniper Square - Technical Lead (Data)
Requirements
• Bachelor's degree in Computer Science, or equivalent work experience • 7-11 years of experience building ETL (Extraction Transform Load) or ELT (Extraction Load Transform) pipelines from scratch • Strong command of relational databases (Postgresql preferred), data modeling and database design • Strong command of Python and experience building production web applications using Python • Experience with cloud-based services (AWS RDS preferred) • Experience developing on (or administering) BI/data visualization platforms (ex. Looker, Tableau, PowerBI, Mode, Data Studio, Domo, QlikView etc.). • Basic understanding of data warehouses such as Amazon Redshift, Google BigQuery, Snowflake etc. • Demonstrated history of translating data into clear and actionable narratives and communicating opportunities and challenges relevant to stakeholders. • You must be flexible and adaptable – you will be operating in a fast-paced startup environment. • Familiarity with data catalog or data governance platforms – open source (e.g. OpenMetadata) or commercial. • Experience building backend services using Python/FastAPI and designing and implementing scalable RESTful and GraphQL APIs • Mandatory Experience authoring modern web applications using ReactJS and TypeScript, and designing reusable UI components and scalable frontend architecture. • Familiarity with patterns such as tool-calling agents, planning/execution loops, and RAG • Demonstrated ability to use modern AI tools to improve velocity and code quality • At Juniper Square, we believe building a diverse workforce and an inclusive culture makes us a better company. If you think this job sounds like a fit, we encourage you to apply even if you don’t meet all the qualifications
Responsibilities
• Design and implement sophisticated data models in SQL. • Work closely with the other Software Engineers to ensure sound, scalable implementation. • Act as a technical expert on our team regarding all things data, especially as the data team grows and evolves. • Introduce new technologies to evolve and enhance our data pipeline capabilities. • Document data models, architectural decisions and data dictionaries to enable collaboration, maintainability and usability of our analytics platforms and code. • Assist with governance, guidance, code reviews, and access controls so that we maintain consistency, quality, and business confidentiality as we scale analytics access across the company and to customers. • Externally: learn our application data schema, and develop a fluency in how to transform it to enhance customers’ decision-making with data. • Internally: guide product and development teams, advising on instrumentation and laying development foundations for product usage reporting. • Fullfill projects with minimal guidance but with an appropriate sense of when and how to collaborate with others. • Build scalable, highly performant infrastructure for delivering clear business insights from a variety of raw data sources.
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