Sr Data Analyst I (Onsite)

Axon•Scottsdale, AZ

2h•Hybrid

About The Position

As a Senior Data Analyst on Axon’s Operations Business Accelerators team, you will own the data architecture and pipelines that support Global Manufacturing Operations, including Manufacturing, Quality, Logistics, and Supply Chain. In this hands-on individual contributor role, you’ll bridge the gap between Axon’s foundational Corporate Data Platform and the domain-specific data needs of Operations. You’ll transform complex operational data from dozens of source systems into trusted, well-governed assets that power reporting, decision-making, automation, and AI-driven analytics. This is an opportunity to build high-impact data infrastructure in a global operations environment where data quality, scalability, and speed directly influence how Axon manufactures, moves, and supports mission-critical products.

Requirements

Bachelor’s degree in Data Analytics, Computer Science, Engineering, Information Systems, Statistics, another quantitative field, or equivalent practical experience.
5+ years of hands-on experience in data analysis, analytics engineering, or data engineering roles, with increasing responsibility for end-to-end data pipeline ownership.
Advanced SQL proficiency, with demonstrated ability to write, optimize, and troubleshoot complex queries across large-scale datasets in cloud data warehouses; Snowflake experience preferred.
Strong working knowledge of cloud infrastructure and services, including Azure Data Factory, Azure Functions, Blob Storage, Azure SQL, AWS, or equivalent platforms.
Experience building and managing data ingestion pipelines, scheduled jobs, and API-based extraction patterns.
Experience with data transformation frameworks such as dbt, including model development, testing, YAML schema definitions, and version-controlled deployment via Git.
Proficiency with Alteryx for data preparation, blending, and rapid prototyping of transformation logic.
Familiarity with BI and visualization platforms such as Sigma, Power BI, or Tableau for validating data models and supporting downstream reporting.
Solid understanding of relational database concepts, data modeling best practices, and how complex source-system tables interrelate across enterprise applications.
Demonstrated ability to work independently, identify data gaps, propose solutions, and deliver production-quality data assets with minimal oversight.
Excellent communication, documentation, and problem-solving skills, with the ability to operate effectively in a fast-paced, global environment and translate technical concepts for non-technical stakeholders.

Nice To Haves

Experience supporting Operations functions such as Manufacturing, Supply Chain, Quality, or Logistics is a strong plus.
Familiarity with ERP systems such as Microsoft D365 Finance & Operations or SAP, hands-on experience with Fivetran or similar ELT platforms, Python scripting, database administration concepts, or relevant certifications such as Snowflake SnowPro, dbt Analytics Engineering, or Alteryx Designer are preferred.

Responsibilities

Own and manage Operations data architecture within Snowflake, including silver/core and gold/mart layer tables that serve as the foundation for Operations analytics and reporting.
Design, build, and maintain custom data ingestion pipelines for source systems not covered by Corporate Data Engineering, including on-premise applications, manufacturing automation databases, and third-party APIs.
Use Azure Data Factory, Azure Functions, Blob Storage, Azure SQL, incremental API extraction patterns, and Parquet-based staging to support scalable and reliable data ingestion.
Partner with Corporate Data Engineering, Enterprise IT Architecture, automation developers, and Operations stakeholders to align on platform patterns, governance standards, and architecture best practices.
Close source-system coverage gaps across high-volume environments, including automation equipment and production lines that generate billions of rows of operational data.
Develop data models that consolidate dozens of source tables into unified, analytics-ready datasets for Manufacturing, Quality, Logistics, and Supply Chain.
Prototype transformation logic in Alteryx, then convert finalized logic into Snowflake SQL using dbt models and YAML schema contracts aligned to Axon’s medallion architecture.
Manage the full development lifecycle for Operations data assets, including dbt model development, testing, documentation, pull requests, code reviews, and deployment coordination.
Build a deep understanding of source-system relationships across ERP, manufacturing execution systems, quality platforms, and supply chain tools, and translate that knowledge into clean, well-documented data flows.
Build and maintain data infrastructure that supports AI, machine learning, advanced analytics, automation solutions, and AI agents.
Support automation developers by providing reliable, well-modeled data assets and collaborating on solutions that combine data pipelines with business process automation.
Mentor junior analysts and business data users, helping build data literacy and technical capability across Global Operations.