Senior Data Analyst

Critical Propulsion•Dallas, TX

About The Position

This role focuses on data modeling and analysis, requiring immediate productivity. The individual will design data structures, taxonomies, and standards to ensure reliable pipelines and usable data products, acting as the gatekeeper for data quality before it moves downstream. The company utilizes a 'swarm model' pairing senior operators with AI agents to improve efficiency and capacity. The first week involves productive delivery, not traditional onboarding, with a focus on defined outcomes and operator autonomy.

Requirements

Ability to build data models from scratch (conceptual, logical, physical).
Experience with various schema types (star, flat, transactional).
Understanding of trade-offs between normalization and denormalization at scale.
Proficiency in extracting and standardizing data from messy, real-world formats (PDF, HTML, XBRL, iXBRL, APIs, flat files).
Experience with agentic development and using AI for data tasks.
Proficiency in Python, SQL, and Spark for data manipulation, analysis, and automation.
Ability to define and enforce data modeling standards.
Strong communication skills, including presenting data-backed evidence.
Ability to operate autonomously.

Nice To Haves

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, including notebooks, Unity Catalog, and Databricks SQL.
Experience using Databricks AI capabilities (Databricks Assistant, AI Functions, Mosaic AI) for data profiling, anomaly detection, or model validation.
Comfort with spec-driven development and writing unambiguous data specs for engineers.
Data visualization experience with Tableau, Power BI, or similar.
Background in consulting or client-facing delivery.

Responsibilities

Build data models from scratch (conceptual, logical, physical), including star schemas, flat schemas, and transactional models.
Extract and standardize data from various formats like PDF, HTML, XBRL, iXBRL, APIs, and flat files.
Embrace agentic development by delegating work to AI agents, critically reviewing their output, and iterating quickly.
Write Python, SQL, and Spark for data manipulation, analysis, and automation.
Define and enforce data modeling standards, conducting analysis to validate compliance, identify anomalies, and catch quality issues.
Communicate findings directly and with evidence, especially when data contradicts beliefs.
Operate autonomously, minimizing unnecessary meetings and documentation.