Ames Construction has been building America for more than 60 years, and the people who work here are the reason we continue to succeed.
We are a full-service, heavy civil and industrial contractor building critical infrastructure, including highways, bridges, mines, dams, rail,and more. Our teams take on challenging projects that keep communities safe, supply chains moving, and the country connected.
At Ames, we are Fueled by Family and Driven by Ownership. That means we look out for one another, take pride in what we build, and take responsibility for our actions, our results, and the long-term health of the company.
Guided by our core values of People, Team, Our Bond, Persistence, and Vision, we do what we say we will do, push through challenges and deliver work we’re proud of.
When you join Ames, you’re joining a company built for long-term success — where skilled people, strong teams, and disciplined execution come together to build careers and a better future.
We are looking for an entry-level Data Analyst to join our team and support the modernization of our company’s data stack using Azure Databricks, GitHub, and Power BI. This role is ideal for someone early in their career who is enthusiastic about data engineering, analytics, AI, and cloud-first modernization. You will gain hands-on experience across the end-to-end data lifecycle—from ingestion through transformation and modeling to reporting—helping build scalable, governed datasets and analytics outputs.
Essential Functions
- Back-End Development (Data Engineering & Modernization):
Building out data pipelines and integrations across data sources to a cloud platform (Lakehouse, Data Warehouse) to support data transformation and modeling using SQL, Python and AI as well as assist with custom app support. - Data Quality and Governance Support:
Implement data validation routines and monitor data integrity across systems. Debug and resolve data quality, pipeline reliability, and performance issues across the data stack. Contribute to data governance efforts by tagging and classifying datasets, maintaining metadata, and supporting compliance with organizational standards using Databricks Unity Catalog. - Front-End Development (Semantic Layer & Reporting):
Help design and publish data models, schemas, and storage to simplify data access for business users. Support the creation and maintenance of reports and dashboards using Power BI, other visualization tools, and AI. Ensure outputs are accurate, user-friendly, and aligned with stakeholder requirements. Partner with security and infrastructure teams to secure and request access from data to reporting via Azure Key Vault, Databricks, custom apps, Power BI - Stakeholder Engagement and Request Intake:
Engage with business users across departments to understand data needs and provide initial support for data requests. Document requirements, assist in scoping tasks, and escalate complex requests to senior team members for further evaluation. - Data Documentation and Best Practices:
Maintain clear and organized documentation of data sources, pipeline logic, and reporting processes. Learn and apply best practices for data engineering, including modular coding, version control, and platform-specific standards. - Skill Development and Continuous Learning:
Actively develop technical skills in Databricks, Py-Spark, SQL, and Python. Understand how data engineering contributes to broader organizational goals such as data democratization, AI readiness, and strategic decision-making.
Qualifications
- Education: 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. Demonstrated ability to build or support data workflows end-to-end (ingestion through transformation to reporting) in a way that improves data reliability and usability.
Technical Skills:
- Experience in building and supporting data visualizations, such as Power BI, Excel, or Databricks Dashboards.
- Familiarity with Github-based workflows and CI/CD fundamentals (branching, pull requests, code reviews) and basic monitoring/data-quality practices.
- Strong skills in coding languages such as SQL, Python, or Py-Spark for data querying and extraction, transformation, and loading (ETL/ELT) processes across Lakehouse and warehouse environments.
- Introductory experience with statistical analysis tools (e.g., Python, R) and data processing frameworks as well as working with structured and unstructured data.
- Understanding data quality assurance practices and data validation techniques.
- Familiarity with end-to-end data platforms, such as Databricks, Azure, or Google Cloud, is a plus.
- Knowledge of custom app building via Microsoft Power Apps and Databricks Apps.
- Familiarity with using AI-assisted tools to improve productivity and code quality while following data security and governance standards.
Soft Skills:
- Demonstrates strong problem-solving skills and a detail-oriented mindset when working with data and code. Proactively identifies data issues and seeks guidance to resolve them.
Working Conditions
- Location – This position will work out of our Burnsville, MN office.
- Office environment – extensive sitting at desk and computer; some standing, bending at the waist, stooping, and reaching required; ability to lift 5-20 pounds occasionally.
- Schedule: M-F, 8am -5pm
- Compensation: $80,000-$105,000
Ames Construction is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.