Data Analyst
Atlanta, GA · Hybrid
Learn more about our Data & Analytics Recruitment solutions.
Axial Search recruits for AI transformation roles across North America, building long-term relationships with leaders across every industry vertical. Apply today to express your interest in this position and others like it. Visit our website to learn more about our process and to find free tools to support your job search — including our live job market dashboard with salary, skills, and hiring-trend data from thousands of AI transformation roles.
What the market looks like
Data analyst roles sit at the entry and early-career end of our dataset, but with real upside — the strongest analyst hires we see move into analytics engineering or data science within two to three years. In the Atlanta financial services market specifically, hiring spans regional banks, fintech startups, and healthcare-adjacent finance, with base compensation generally in an $85K–$130K range. Excel, SQL, and a modern BI tool (Power BI, Tableau, or Looker) remain table stakes; the analysts who stand out are the ones who automate their own work and keep asking better questions.
Job responsibilities
Partner with business teams to turn data into decisions via dashboards, deep dives, and ad-hoc analysis
Build and maintain critical reports and self-serve BI assets in Power BI, Tableau, or Looker
Write SQL against the data warehouse and work closely with data engineering on definitions
Lead A/B test readouts and funnel analyses for business partners
Document metrics definitions and evangelize good data practice across the team
Continuously look for opportunities to automate, standardize, and scale analytics work
Dig into unexpected patterns in the data rather than just shipping the dashboard someone asked for
Contribute to the analytics engineering practice as your technical skills grow
Candidate requirements
2+ years of analytics experience with strong SQL fundamentals
Hands-on experience with at least one major BI tool (Power BI, Tableau, or Looker)
Comfortable in a cloud data warehouse (Snowflake, BigQuery, or Redshift)
Strong statistical foundation — able to read and run A/B tests correctly
Excellent written and verbal communication with non-technical stakeholders
Excel and PowerPoint fluency, with the ability to tell a clear story with data
