Analytics Engineer

HelioCampus•Bethesda, WI

1d•Hybrid

About The Position

HelioCampus was founded with the purpose of helping college & university leaders navigate today’s growing pressures. As one of EdTech’s most steadily growing companies, our roots in higher ed ground us in the critical nature of this work. We help our clients navigate today’s high stakes with data and Institutional Performance Management practices. Together with our clients, we chart a path to sustainability by borrowing practices from the most successful businesses. We approach our work with a “we’re on it” attitude that the higher ed community has come to know and expect from our team. We’re data geeks to our core, committed to simplifying the toughest challenges and operating with transparency. Our most successful team members are change agents who love a challenge. As an Analytics Engineer, you will play a key role in transforming data into meaningful insights that drive institutional decision-making. You’ll partner with cross-functional teams to design scalable data solutions, improve data quality, and deliver impactful analytics to our clients.

Requirements

2–4 years of experience in analytics engineering, data engineering, or a related field.
A bachelor’s or master’s degree in computer science, data analytics, information systems, or a related discipline.
Strong programming skills in languages such as Python, SQL, Scala, or Java.
Experience working with relational and/or NoSQL databases.
Hands-on experience building and optimizing ETL/ELT pipelines.
Familiarity with big data technologies such as Apache Spark or Hadoop.
Experience with BI tools and building dashboards (e.g., Tableau, Power BI, Looker, etc.).
Strong problem-solving skills with the ability to work through moderately complex data challenges.
Excellent communication skills with the ability to translate technical concepts into business insights.
A collaborative mindset and growing ability to lead projects or mentor others.

Nice To Haves

Experience with cloud platforms such as AWS, Azure, or GCP.
Exposure to data warehousing concepts and modern data stack tools (e.g., dbt, Snowflake, Redshift, BigQuery).
Experience with real-time or stream-processing systems.
Background working with higher education data or in a consulting environment.
Familiarity with data governance and data modeling best practices.

Responsibilities

Design and implement robust, scalable data pipelines to support analytics and reporting needs.
Build, maintain, and optimize ETL/ELT processes across cloud-based data platforms.
Develop and automate reporting solutions and interactive dashboards using modern BI tools.
Ensure data integrity, quality, and governance across multiple data sources.
Apply statistical and analytical techniques to generate actionable business insights.
Collaborate with engineers, analysts, and client stakeholders to translate business needs into technical solutions.
Lead smaller projects or own key components of larger initiatives.
Contribute to continuous improvement efforts, including performance tuning and process automation.
Mentor junior team members and support knowledge sharing across the team.