Analytics Engineer, Gemini

• 2+ years experience developing a BI applications (Tableau/Looker/Power BI, etc)
• Advanced skills with SQL are a must
• 2+ years experience in custom ETL design, implementation and maintenance
• 2+ years experience with schema design and dimensional data modeling
• Experience making sense of data and developing actionable insights
• Experience with one or more MPP databases (Redshift, Bigquery, Snowflake, etc)
• Experience with one or more ETL frameworks (Custom, DBT, Databricks, etc)
• Experience with statistics, machine learning and generative AI
• Strong software engineering skills in any server side language, preferable Python
• Experienced in working collaboratively across different teams and departments
• Strong technical and business communication

Desirable

• As a member of our data team, you'll deliver high quality work while solving challenges that impact the whole or part of the team's data architecture
• You'll update yourself with recent advances in Big data space and provide solutions for large-scale applications aligning with team's long term goals
• Your work will help resolve complex problems with identifying root causes, documenting the solutions, and implementing Operations excellence (Data auditing, validation, automation, maintainability) in mind. Communicating your insights with leaders across the organization is paramount to success
• Design, architect and implement best-in-class Data Warehousing and reporting solutions
• Partner with product managers, data engineers and other functions to drive insights for the firm
• Design, automate, build, and launch scalable, efficient and reliable data pipelines into production using Python
• Design, build and enhance dimensional models for Data Warehouse and BI solutions
• Perform analysis to derive actionable insights for key stakeholders
• Perform root cause analysis and resolve production and data issues
• Create test plans, test scripts and perform data validation
• Tune SQL queries, reports and ETL pipelines
• Build and maintain data dictionary and process documentation
• Research new tools and technologies to improve existing processes