Senior Data Analyst (Houston)

Job Description

We are looking for a Data Analyst who is curious and technically-minded exploring data within our modern stack (AWS & Databricks) to ensure accuracy through profiling and building a robust data fabric layer that empowers AI & Analytics use cases. You will act as the bridge between our Business and Development teams. Your job is to discover what the data says, listen to what the business needs, and translate those needs into technical requirements for the developers.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Key Responsibilities

Data Discovery: Explore raw data to find trends and solve business use cases

Bridge the Gap: Work with Business teams to understand their goals and transform them into clear technical plans for the Dev team.

Data Profiling: Check data for quality and accuracy and usability making sure we can trust the numbers.

The Fabric & Semantic Layer: Help organize data so that scattered data is stitched to make sense to regular business users.

Skills Needed

Advanced SQL: You should be an expert at writing queries to pull and analyze data.

AWS & Databricks: Familiarity with cloud storage (AWS) and using Databricks to process data.

Data Design: An understanding of how to structure data for AI use cases and easy reporting.

A natural "liking" for digging into data to find RCA.