Senior Data Engineer

ANA•Henderson, NV

18h•$130,000 - $146,000•Onsite

About The Position

About ANA: Join a recognized industry leader - Alliance North America was proudly named a 2025 Top Workplace in the Manufacturing Industry, an honor based entirely on feedback from our own employees about our culture, values, and workplace experience. Alliance North America was established in 2017 and is proud to be the sole North American supplier of AIRMAN Power Generators, AIRMAN Air Compressors, and ANA’s patented EBOSS® Hybrid Energy System and Smart load bank system.  Our commitment to our customers is to Make their World Easier, by answering the phone, understanding their needs, and taking ownership to provide them solutions. With a large parts inventory and more than 90% of all orders shipping within 24 hours, you never have to worry about spare parts. We help keep your fleet in top condition with our world class Support Department, who are always ready to help and be a resource by providing training on our equipment. ANA is headquartered in Henderson, Nevada, with locations in Cypress, California, and Spartanburg, South Carolina. ANA is growing and scaling, and we are seeking a Senior Data Engineer to join our growing team in an onsite position in Henderson, Nevada. As a Senior Data Engineer, you will have the opportunity to transform complex data into actionable insights that drive strategic decision-making. This role partners with business leaders, product teams, and engineers to design, build, and optimize data models, dashboards, and analytics solutions. This position is fully onsite, and the work schedule is weekdays from 8:00 am – 5:00 pm.   This role reports to the Business Applications Support Desk Manager.

Requirements

Bachelor's degree in information systems, Finance, or related field, preferred.
5+ years of experience in data engineering, analytics engineering, or BI development.
Proven experience building and maintaining enterprise data warehouses and data lakes.
SQL: Expert level — queries, advanced joins, stored procedures, optimization.
Azure Cloud: Hands-on experience with Azure Synapse, Data Factory, Data Lake Storage, Azure SQL, and/or Databricks.
ETL/ELT Tools: Experience with Azure Data Factory, SSIS, Databricks, or similar.
BI Tools: Strong experience with Power BI (DAX, modeling), Tableau, or equivalent.
Programming: Working knowledge of Python or R for advanced analytics.
Data Modeling: Dimensional modeling and performance-focused design.
Strong analytical thinking and problem-solving skills
Excellent communication and data storytelling abilities
Ability to manage multiple projects and priorities in a fast-paced environment

Responsibilities

Stakeholder Collaboration: Engage with business leaders and cross-functional teams to gather requirements, understand challenges, and translate needs into actionable data solutions.
Partner with business stakeholders to understand analytical needs and define project scope.
Present complex data findings clearly to technical and non-technical audiences, driving data literacy.
Technical Expertise: Write and optimize complex SQL queries for data extraction and manipulation.
Understand data modeling, data mapping, and data integration techniques.
Stay current with BI software, data science trends, and engineering best practices.
Data Platform Architecture & Engineering: Design, implement, and maintain scalable data pipelines for ingestion, transformation, and delivery.
Own structural design and optimization of the enterprise data warehouse and data lakes in Azure.
Implement best practices around architecture, performance, modularity, and reusable components.
Azure & Cloud Infrastructure: Implement and manage Azure data services (e.g., Azure Synapse Analytics, Data Factory, Data Lake Storage, Databricks).
Monitor and optimize cloud costs, performance, and security for data workloads.
Work with security and infrastructure teams to enforce governance and compliance.
ETL / ELT & Data Integration: Build robust ETL/ELT processes for structured and unstructured data sources.
Ensure data lineage, transformation rules, and metadata are well documented.
Optimize data workflows for performance, reliability, and scalability.
Data Modeling & Quality: Define and maintain enterprise data models and schemas (star/snowflake, fact/dimension).
Implement data quality controls, validation frameworks, and monitoring.
Investigate and resolve data integrity issues with root-cause analysis.
BI & Reporting: Design and build interactive dashboards and reports (Power BI, Tableau).
Collaborate with BI developers to translate business logic into technical specs.
Ensure dashboards meet performance, usability, and accuracy standards.
Advanced Analytics Support: Support analytical and statistical analysis (regression, forecasting) using SQL, Python, or R.
Enable data scientists and analysts with clean, well-structured datasets.
Continuous Improvement & Mentorship: Identify opportunities to improve data processes, tools, and architecture.
Provide guidance, training, and best practices to engineering and BI team members.
Lead evaluation and adoption of new tools or technologies.
Other duties as assigned