Data Analyst

Senior Data Analyst – Enterprise Data & Insights

We are seeking a highly analytical Senior Data Analyst to work with large, complex enterprise datasets and turn ambiguous data into meaningful insights and actionable business recommendations.

This role is ideal for someone who enjoys digging into messy data, figuring out what can be trusted, identifying patterns and discrepancies, and translating findings into a clear story for business and technical stakeholders.

This is an analytics-focused role, not a Data Engineering position. While you will work within an environment that includes Databricks, Spark, ETL processes, and enterprise data infrastructure, your focus will be on analyzing, investigating, validating, and interpreting data—not building production data pipelines.

What You’ll Do

• Analyze large, complex enterprise datasets using SQL and Databricks

• Investigate data quality, coverage, duplication, inconsistencies, discrepancies, and edge cases

• Determine which data is reliable and apply business logic when source data is incomplete, inconsistent, or poorly documented

• Identify meaningful patterns, trends, and opportunities within the data

• Define, analyze, and validate business metrics and KPIs

• Translate analytical findings into clear insights and actionable recommendations

• Develop compelling data stories that explain not only what the data shows, but why it matters

• Compare and reconcile data across multiple systems and sources

• Support analysis related to enterprise data migrations, transformations, and validation

• Partner closely with business and technical stakeholders to understand questions, investigate issues, and communicate findings

• Work within data environments involving Databricks, Spark, ETL processes, and complex enterprise data flows

What We’re Looking For

• 5–10 years of experience in data analytics, business intelligence, data analysis, or a similar analytical role

• Bachelor’s degree in Computer Science, Technology, Data Analytics, or a related field

• Advanced SQL skills with experience querying and analyzing large enterprise datasets

• Strong analytical and investigative problem-solving skills

• Proven ability to work with large, messy, or ambiguous datasets

• Experience identifying and resolving data quality, duplication, coverage, and consistency issues

• Ability to take an ambiguous business problem and determine how to use available data to answer it

• Experience deriving insights and translating them into business recommendations

• Strong data storytelling and communication skills

• Ability to explain complex findings clearly to both technical and non-technical stakeholders

• Strong attention to detail and willingness to investigate anomalies and edge cases

Preferred Experience

• Hands-on Databricks experience for data exploration, investigation, and analytics

• Working knowledge of Spark

• Understanding of ETL processes, data flows, and data validation

• Experience supporting enterprise data migrations or complex data environments

• Experience developing or analyzing KPIs and business metrics

• Familiarity with graph-style data models, knowledge graphs, or ontologies is a plus

What This Role Is — and Isn’t

The strongest candidate is an analytics professional first who also understands the technical environment surrounding enterprise data.

You should be comfortable with Databricks, Spark, ETL concepts, and data flows, but your primary strength should be investigating data and extracting insights from it.

This role is not focused on:

• Building production ETL pipelines

• Data pipeline engineering

• Data synchronization

• Infrastructure engineering

• Production performance optimization

• Traditional Data Engineering ownership

If your strength is taking complex data, determining what can be trusted, uncovering meaningful insights, and communicating what the business should do with those insights, this role could be a strong fit.