Data Analyst – Entry-level Data

Job Description

Data Analyst | Ames Construction

The Tone:
This is a full-time role at Ames Construction, located in Burnsville, MN. Ames Construction has been building critical infrastructure across America for over 60 years, including highways, bridges, and dams. This entry-level Data Analyst role is pivotal for supporting the modernization of the company’s data stack, leveraging cloud technologies to build scalable, governed datasets and analytics outputs that will drive informed decision-making.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: In-person, Burnsville, MN
• Pay: $80000–$105000 yearly
• Mission: Support the modernization of the company’s data stack, building scalable, governed datasets and analytics outputs from ingestion to reporting.
• Tech Stack: Azure Databricks, GitHub, Power BI, SQL, Python, Py-Spark, Excel, Databricks Dashboards, Databricks Unity Catalog, Azure Key Vault, Microsoft Power Apps, Databricks Apps, R

What You’ll Actually Do
• Data Pipeline Development: Build data pipelines and integrations across various data sources to cloud platforms like Lakehouse or Data Warehouse using SQL, Python, and AI, also assisting with custom app support.
• Data Quality & Governance: Implement data validation routines, monitor data integrity, debug data quality and pipeline issues, and contribute to data governance efforts by tagging and classifying datasets with Databricks Unity Catalog.
• Reporting & Data Modeling: Design and publish data models, schemas, and storage to simplify data access, supporting the creation and maintenance of accurate and user-friendly reports and dashboards using Power BI and AI.
• Stakeholder Engagement: Engage with business users across departments to understand data needs, provide initial support for requests, document requirements, and assist in scoping tasks.
• Data Documentation & Skill Development: Maintain clear documentation of data sources, pipeline logic, and reporting processes, while actively developing technical skills in Databricks, Py-Spark, SQL, and Python.

The Must-Haves
• Background: Bachelor’s degree in data science, Statistics, Computer Science, Business, or equivalent work experience.
• Experience: Internship, academic, or project-based experience in data engineering, analytics engineering, or a related field, including basic data modeling and relational database concepts, with a demonstrated ability to build or support end-to-end data workflows.
• Skills: Strong skills in coding languages such as SQL, Python, or Py-Spark for ETL/ELT processes, experience in building and supporting data visualizations with Power BI or Excel, and familiarity with Github-based workflows and CI/CD fundamentals.
• Bonus: Familiarity with end-to-end data platforms such as Databricks, Azure, or Google Cloud, knowledge of custom app building via Microsoft Power Apps and Databricks Apps, and familiarity with using AI-assisted tools for productivity.