Jobs via Dice
Data Analyst
Location:
Houston, TX
Type:
Full-Time
Department:
Data & Insights
Reports to:
Data Analytics Manager / Head of Analytics
Core Responsibilities
Query and analyze large datasets using SQL to answer business questions.
Build and maintain interactive dashboards in Tableau, Looker, or Power BI.
Track and define KPIs: Conversion rates, retention, revenue per user, operational efficiency.
Conduct ad-hoc analyses: funnel optimization, cohort studies, A/B test results, forecasting.
Support cross-functional teams: Marketing, Product, Finance, Ops with data‑backed recommendations.
Ensure data quality: Validate sources, audit pipelines, document assumptions.
Automate recurring reports to eliminate manual work and enable self‑service.
Present insights to stakeholders via concise slides, clear narratives, confident Q&A.
What You Bring Must-Have
2‑4 years of data analysis or business intelligence experience.
Expert‑level SQL: Complex joins, CTEs, window functions, query optimization.
Visualization mastery: Tableau (preferred), Looker, or Power BI; clean, interactive, insightful visualizations.
Statistical foundation: knowledge of p‑values, confidence intervals, regression.
Excel/Google Sheets power user: Pivot tables, VLOOKUP, data validation, macros.
Business curiosity: asks why five times and follows the data.
Bachelor’s in Statistics, Economics, Math, Computer Science, or equivalent experience.
Nice-to-Have
Python or R for automation, modeling, or advanced analytics (pandas, statsmodels).
Experience with product analytics tools (Amplitude, Mixpanel, Heap).
dbt for data modeling and transformation.
Cloud data platforms: Snowflake, BigQuery, Redshift.
Experimentation frameworks: Optimizely, Eppo, or custom A/B platforms.
Background in SaaS, e-commerce, fintech, or marketplaces.
Tech Stack
Data Warehouse: Snowflake / BigQuery / Redshift
BI Tools: Tableau (preferred) / Looker / Power BI
Transformation: dbt Core
Querying: SQL, Excel, Google Sheets
Scripting: Python (pandas, matplotlib), R
Tracking: Segment, Snowplow, Google Analytics
Collaboration: Slack, Jira, Notion
#J-18808-Ljbffr
Houston, TX
Type:
Full-Time
Department:
Data & Insights
Reports to:
Data Analytics Manager / Head of Analytics
Core Responsibilities
Query and analyze large datasets using SQL to answer business questions.
Build and maintain interactive dashboards in Tableau, Looker, or Power BI.
Track and define KPIs: Conversion rates, retention, revenue per user, operational efficiency.
Conduct ad-hoc analyses: funnel optimization, cohort studies, A/B test results, forecasting.
Support cross-functional teams: Marketing, Product, Finance, Ops with data‑backed recommendations.
Ensure data quality: Validate sources, audit pipelines, document assumptions.
Automate recurring reports to eliminate manual work and enable self‑service.
Present insights to stakeholders via concise slides, clear narratives, confident Q&A.
What You Bring Must-Have
2‑4 years of data analysis or business intelligence experience.
Expert‑level SQL: Complex joins, CTEs, window functions, query optimization.
Visualization mastery: Tableau (preferred), Looker, or Power BI; clean, interactive, insightful visualizations.
Statistical foundation: knowledge of p‑values, confidence intervals, regression.
Excel/Google Sheets power user: Pivot tables, VLOOKUP, data validation, macros.
Business curiosity: asks why five times and follows the data.
Bachelor’s in Statistics, Economics, Math, Computer Science, or equivalent experience.
Nice-to-Have
Python or R for automation, modeling, or advanced analytics (pandas, statsmodels).
Experience with product analytics tools (Amplitude, Mixpanel, Heap).
dbt for data modeling and transformation.
Cloud data platforms: Snowflake, BigQuery, Redshift.
Experimentation frameworks: Optimizely, Eppo, or custom A/B platforms.
Background in SaaS, e-commerce, fintech, or marketplaces.
Tech Stack
Data Warehouse: Snowflake / BigQuery / Redshift
BI Tools: Tableau (preferred) / Looker / Power BI
Transformation: dbt Core
Querying: SQL, Excel, Google Sheets
Scripting: Python (pandas, matplotlib), R
Tracking: Segment, Snowplow, Google Analytics
Collaboration: Slack, Jira, Notion
#J-18808-Ljbffr