About the position
As a Senior Analytics Engineer at Upstart, you will design and develop robust and scalable data models for analytical stakeholders to empower them to retrieve meaningful insights. Our analytics engineering team is centralized within the company and partners closely with data engineering, data platform, software engineers, ML engineers and cross functional analytics squads to stitch together datasets to create data models that are ready for consumption. In addition to architecting data models, we implement Analytics Engineering best practices around Data Governance, Data Quality, Data Orchestration and pipeline optimization. We enable analysts to think like software engineers by defining, documenting and ensuring adoption of best practices when making contributions to the analytical code-base.
Responsibilities
- Understand how data is produced and consumed at a deep level - you will need to be extremely collaborative with the teams that produce and consume the data to create an end-to-end solution that maximizes the value of our data
- Lead efforts to design data models and build curated data sets that are the foundation of reporting and analytics at Upstart
- Collaborate with data engineers and data platform teams to create analytics pipelines
- Meet consumers of data where they are by wearing an educator's hat and training them on how to use BI tools and dashboards
- Be a close strategic partner to analytics squads to participate in decision making on the analytics road map for Upstart
Requirements
- 5+ year(s) of experience as a Data Engineer / Analytics Engineer / BI Engineer
- Strong understanding of data modeling concepts in both transactional and analytical databases
- Proven ability to lead cross-team projects to create data models for analytics/reporting purposes
- Excellent communication and collaboration skills, particularly when explaining technical or complex matters to less technical co-workers
- Expertise in SQL, Python, and ETL optimization techniques
Nice-to-haves
- Familiarity with business intelligence visualization tools such as Mode, Looker, Tableau, Power BI, etc.
- Experience creating curated data models using a data mesh architecture
- Experience with cloud computing platforms such as Amazon Web Services (AWS), Azure and/or Google Cloud
- Experience with building Looker data models (LookML), analytics engineering frameworks like dbt, orchestration tools like Airflow, schema design, and dimensional data modeling
- Thorough understanding of data lake/warehouse architectures (BigQuery, Databricks, Redshift)
