Senior Data Analyst

What you'll own

Data modeling and analysis with a team looking for immediate productivity. You design the data structures, taxonomies, and standards that make pipelines reliable and data products usable. You're the person who makes sure the data is right before it moves downstream.

How we work

Critical Propulsion amplifies human delivery. Our swarm model pairs 3-4 senior operators with AI agents to cut cycle times 30-50% and multiply effective capacity 2-5x versus traditional teams. No sprint theater.

Week 1 is productive delivery, not onboarding. We define outcomes and trust operators to get there.

What we expect

• You build data models from scratch. Conceptual, logical, physical. Star schemas, flat schemas, transactional models. You've done this for green-field projects and you understand the trade-offs between normalization and denormalization at scale.
• You extract and standardize data from messy, real-world formats: PDF, HTML, XBRL, iXBRL, APIs, flat files. You don't flinch at ugly source data.
• You embrace agentic development. You don't treat AI as autocomplete. You delegate real work to AI agents, review their output critically, and iterate fast. You see this as the future of how data work gets done, not a novelty.
• You write Python, SQL, and Spark to manipulate, analyze, and automate. You're not just a GUI modeler. You write code to solve data problems.
• You define and enforce data modeling standards. You conduct analysis to validate compliance, identify anomalies, and catch quality issues before they compound.
• You communicate directly. When the data doesn't support what someone wants to believe, you say so with evidence, not a caveat-filled email.
• You operate autonomously. No status meetings that could be a message. No decks that could be a decision.
  
  

What we don't filter on

• Years of experience as a number. If you can model data for a swarm shipping in 5-day pulse cycles, the number on your resume is irrelevant.
• Specific tooling as a prerequisite. We care about data modeling judgment and analytical instinct, not which vendor's logo is on your resume.
• Pedigree. No school or company name substitutes for demonstrated ability to build data models that hold up in production.
  
  

Nice to have

• Deep experience with data modeling tools like Erwin, PowerDesigner, or equivalent.
• Strong SQL skills across relational and cloud databases: SQL Server, PostgreSQL, Snowflake, BigQuery, or Redshift.
• Familiarity with Azure cloud data services: Data Lake, Data Factory, Azure SQL.
• Experience with graph databases (Neo4j) or multiple storage formats (Parquet, AVRO, Delta).
• Hands-on experience with Databricks for data modeling, analysis, and exploration. You've used notebooks, Unity Catalog, and Databricks SQL to build and validate models at scale, not just run ad hoc queries.
• Experience using Databricks AI capabilities: Databricks Assistant, AI Functions, or Mosaic AI for accelerating data profiling, anomaly detection, or model validation workflows.
• Comfort with spec-driven development. You've written data specs that engineers can build pipelines from in a single pulse cycle without ambiguity.
• Data visualization experience with Tableau, Power BI, or similar.
• Background in consulting or client-facing delivery. You've worked with stakeholders who care about the data, not just the dashboard.
  
  

What you get

• A team where everyone builds. No layers of management between you and the work.
• AI agents as real teammates. You'll use AI tooling to accelerate analysis, modeling, and documentation.
• Pulse cycles that create natural rhythm without traditional sprint overhead (KT +75%, Rework +60%, Mgmt +45% in typical sprint models).
• Direct client impact. Your data models hit production in days, not quarters.
• Competitive comp sized for senior operators, not blended-team billing rates.
  
  

How to apply

Send us something that shows how you think about data. A model you've built, a write-up of a hard data problem you solved, a schema design you're proud of. Skip the cover letter unless you actually want to write one.

Real conversation. No fluff.