Sr Data Analyst I (onsite)

Axon Axon · Enterprise · AZ · 1502 OPS - Operations (Hardware)

This role focuses on owning and managing data architecture and pipelines for Global Manufacturing Operations, transforming operational data into assets for reporting, decision-making, automation, and AI-driven analytics. The individual will build and maintain data infrastructure supporting AI/ML and AI agents, working with cloud services like Azure Data Factory and Snowflake, and using tools like dbt and Alteryx.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. Partner with Corporate Data Engineering, Enterprise IT Architecture, automation developers, and Operations stakeholders to align on platform patterns, governance standards, and architecture best practices.
  5. Build and maintain data infrastructure that supports AI, machine learning, advanced analytics, automation solutions, and AI agents.

Skills

Required

  • 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.
  • 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 have

  • 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.

What the JD emphasized

  • Own and manage Operations data architecture within Snowflake
  • Design, build, and maintain custom data ingestion pipelines
  • Build and maintain data infrastructure that supports AI, machine learning, advanced analytics, automation solutions, and AI agents.

Other signals

  • Build and maintain data infrastructure that supports AI, machine learning, advanced analytics, automation solutions, and AI agents.
  • Transform complex operational data from dozens of source systems into trusted, well-governed assets that power reporting, decision-making, automation, and AI-driven analytics.