Analytics Engineer
The Analytics Engineering team at CircleCI will work to apply software engineering methodologies to the production and maintenance of analytics code and transform raw data into consumable information and business logic. The team will build a workflow that tests data to ensure it is of high quality, documents all business logic, and ensures data models are running optimally in a production environment. The team will be instrumental in growing the velocity of the analytics process and will improve the quality of data by bringing a deep understanding of what the business needs into the transformation process! We’re now looking for someone who brings the experience and entrepreneurial mentality to join this team and contribute to the growth of the company.
What you’ll do:
- Work on high impact projects that improve data availability and quality, and provide reliable access to data for the rest of the business.
- You’ll be the go-to data specialist at the company, and will help bridge the gap between understanding business needs and knowing how to craft efficient, usable data models.
- Play a critical role in establishing protocols for how data is stored, managed, and used to ensure data integrity, security, and privacy.
- Responsible for defining how the data will be ingested, consumed, integrated, and managed by different data entities and business systems, such as HubSpot, Salesforce, and NetSuite.
- Transform raw data into a format that can be easily analyzed using tools such as dbt or SQL.
- Ensure data accuracy and reliability by writing tests to guarantee the integrity of the transformed data.
- Help define the data and analytics strategy and technical direction, advocate for standard methodologies, and investigate new technologies.
What we're looking for:
- Experience: 3+ years experience as a data analyst or analytics engineer and prior experience with software engineers or software engineering workflows
- Technical Skills: Proficient in SQL with experience programming in Python or another high-level language. Understanding of schema design for analytics and the operational needs of data pipelines. Just as comfortable getting quick answers with Excel
- A strong understanding of data quality testing
- Strong understanding of data modeling and data warehousing concepts
- Experience in the design and development of data pipelines using SQL, dbt, & python
- Ability to craft functional and user-friendly data products such as data models and dashboards
- Experience working with code based managed solutions such as Snowflake, Looker, and dbt preferred.
- Some other applications you may work with are Fivetran, Mode, Airflow, Hightouch, and Hubspot.
- Technical Education: Relevant experience ora bachelor’s degree in a technical or quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Economics, or Finance) or equivalent experience
- Soft Skills and values: some text
- Engineering mind-set: You test assumptions; perform research for novel solutions to understand trade-offs between precision and effort.
- Problem-solving: You bring curiosity and a strong interest in data, discovery, and an entrepreneurial mentality to your work
- Openness: You’re open to questioning your assumptions and being questions, and resilient
- Communication: You’re an effective communicator across technical and business audiences
- Planning: You have an affinity for structure and efficiency and are able to balance planning and execution, and are able to optimize for incremental value delivery. You manage partner expectations gracefully
- Ambitious, collaborative, and empathetic values
United States Base Pay Range: $118,000—$170,000 USD
Canada Base Pay Range: $95,000—$143,000 CAD
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