Lead Engineer (Data)

Summary

Join Juniper Square's growing Data Engineering Team as a Senior Data Engineer to build and evolve data and reporting experiences. You will design and implement data models in SQL, collaborate with software engineers, and act as a technical expert on data. Responsibilities include building data pipelines, introducing new technologies, documenting data models, and assisting with governance. You will also guide product and development teams on instrumentation and reporting, and build scalable infrastructure for delivering business insights. The role requires strong SQL, Python, and database skills, along with experience in ETL/ELT pipelines and cloud services. Juniper Square offers various work arrangements, from fully remote to working in physical offices.

Requirements

• Bachelor's degree in Computer Science, or equivalent work experience
• 8+ 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

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 customer’s decision-making with data
• Internally: guide product and development teams, advising on instrumentation and laying development foundations for product usage reporting
• Fulfill 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