What You’ll Do
- You will be responsible for building and maintaining the data layer for our analytics stack, top to bottom. Part data engineer, part data analyst, and part the connective tissue in-between, your responsibilities will span from raw data, up through cleaned, organized and analyzable data. You’ll apply software engineering practices like version control, automated testing, documentation, code review and continuous integration to our data stack. In a particular week, you will find yourself:
- Writing SQL in dbt to build robust, extensible, and performant data models in a cloud-based data warehouse that will drive business intelligence for the company.
- Working alongside business users and data analysts, designing and building data models that unlock their data discovery and analyses.
- Working with engineers to understand existing data models and implementing new data structures to unlock business insights and data comprehension for all.
- Improving organizational capacity by owning data discovery and cataloging tools that create visibility into business processes, especially for non-technical users.
- Troubleshooting, improving and scaling existing data models and reports.
Required Qualifications, Skills, & Abilities
- 6+ years of work experience as an analytics engineer, data engineer or data analyst.
- 4+ years of advanced SQL scripting, within a version controlled repository, with a demonstrated ability to refactor highly complex SQL queries to optimize performance.
- 3+ years of coding in dbt or similar transformation tools.
- Excellent data discovery and analytical skills to manage complex business data requirements and data platforms without much guidance.
- Strong communication skills with both business and technical stakeholders.
- Track record of requirements gathering, solutioning and documenting data models.
- Strong understanding of data quality and testing methodologies.
- Experience with monitoring and/or troubleshooting ETL pipelines within Airflow / Python.
- Experience working with GTM teams (Marketing, Sales, Customer Success) and third party tools such as Salesforce, Hubspot or Rev.io.
Preferred Experience
- 3+ years experience with data warehouse cataloging with proven ability to deliver end-to-end visibility and maximize the value of data.
- 2+ years experience building data models with dbt in a cloud based data warehouse platform.
- Experience in data science, building both the foundation and models required to implement machine learning solutions.
- Experience with deploying DBT data models with CI/CD.
- Building data warehousing from large scale transactional data stores and 3rd party systems.
- Experience supporting product analytics via clickstream datasets or tools such as Mixpanel.
- Embedded analytics / BI reporting data models (e.g. looker / cubejs)
- Knowledge of database permissions management
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