Data Analyst - SQL / Databricks

Tenable•Columbia, MA

1d•Hybrid

About The Position

As a Data Analyst in our Business Intelligence organization, you will turn operational and customer data into actionable reports and dashboards that drive business decisions. You will partner directly with internal business teams, such as sales compensation, to gather reporting requirements, document technical specifications, and build user friendly data assets. Your primary hands-on work will involve writing SQL views and building dashboards directly within Databricks using data populated by our engineering team. A key aspect of this role is context engineering, where you will add structured descriptions and metadata to tables, views, and columns so that our data is easily discoverable and accurately queried by AI tools like Claude. Additionally, you will validate report accuracy, monitor data quality, and maintain documentation of your reporting logic to ensure long-term reliability. You will have the opportunity to build and scale the business reporting layer within Databricks. You will be part of a globally distributed team of data professionals. This role is designed for someone who wants to grow their analytical skills in a collaborative, business facing environment. Leverage modern AI coding agents, such as Databricks' Genie or Claude, to assist in writing and optimizing your queries.

Requirements

2 to 4 years of experience in a business intelligence, reporting, or data analyst role.
Fundamental working proficiency in SQL, including an understanding of select statements, order of operations, joins, aggregations, and filtering.
Basic to working proficiency with Databricks, a comparable lakehouse, or cloud data platform such as Snowflake.
Experience building dashboards and presenting data visually using tools like Databricks native dashboards, Tableau, Power BI, or Looker.
Strong written and verbal communication skills to effectively gather requirements from non-technical business stakeholders and translate them into usable data assets.
A detail oriented mindset with comfort in documenting data objects, definitions, and logic for downstream users.

Nice To Haves

Prior experience writing table and column descriptions or metadata to support data catalogs, semantic layers, or natural language query tools.
Exposure to Python or PySpark within Databricks notebooks.
Familiarity with analytics engineering practices, such as dbt, or version control systems like Git.
Experience working in enterprise software, cybersecurity environments.

Responsibilities

Turn operational and customer data into actionable reports and dashboards that drive business decisions.
Partner directly with internal business teams, such as sales compensation, to gather reporting requirements.
Document technical specifications.
Build user friendly data assets.
Write SQL views and build dashboards directly within Databricks.
Add structured descriptions and metadata to tables, views, and columns (context engineering).
Validate report accuracy.
Monitor data quality.
Maintain documentation of reporting logic.