Key skills
SQLPythonData modelingETL optimizationBusiness intelligence toolsCloud computingLooker data modelsCollaboration skillsCommunication skillsAIETLData LakeAnalyticsLookerBIBusiness IntelligenceTableauPower BIBigQueryRedshiftDatabricksAirflowdbtAWSAmazon Web ServicesAzureGoogle CloudCommunicationDecision MakingCollaboration
About this role
Upstart is an AI lending marketplace dedicated to reducing the cost and complexity of borrowing for Americans. As a Senior Analytics Engineer, you will design and develop robust data models and collaborate with various teams to create analytical solutions that empower stakeholders with meaningful insights.
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
- 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)