Data Analyst

MUST:

• 5+ years in a data analyst role
• Very strong with SQL- must understand CTEs, recursive query patterns, understanding performance is paramount, knowing sql well enough to tune equerries to optimize perofmrance and make quqeries easy to read
• Strong experience taking business requirements and then translating to actionable steps for analytics engineers/data engineers
• Ability to build structured business requirements based off of the data from exploratory work they’re doing, gather requirements from business
• Experience with documentation- especially with documenting assumptions and their process
• Experience working within Databricks to then send to analytics engineers for visualization layer
• Understands high level business objectives + experienced in working with very vague business requirements
• Experience working with a backlog
• Experience working with data engineers and analytics engineers and giving/asking for updates from them
• Not afraid to jump in, make messy data clean + Experience being curious and proactive about the data

PLUS:

• Powerbi visualization experience or visualization experience in general
• Data modeling- great not fully required

Day to day:

The Data Analyst partners with business stakeholders to understand system processes, business objectives, and the data available across various systems. They conduct data discovery and exploratory analysis to identify, validate, and clean data, determine where usage and other business-critical information is stored, and assess whether existing data meets business needs or requires additional sourcing. They translate business requirements into clear, actionable requirements for analytics and data engineering teams, identifying specific data fields, sources, transformations, and processes needed to move data into production. They use advanced SQL, including CTEs and recursive query patterns, to extract, analyze, and optimize data while ensuring queries are accurate, efficient, and maintainable. They serve as a data expert within Databricks, bringing data together for analytics and visualization while proactively investigating data quality issues and making complex or messy data usable. They manage and communicate progress against a project backlog, follow up with engineering teams on project updates, and work independently when requirements are vague or evolving. They document assumptions, processes, findings, and requirements to ensure clarity and consistency across teams. They support usage-based analytics and collaborate with Power BI and analytics teams to deliver reporting and visualizations, with hands-on Power BI experience serving as a strong plus.