Junior Business Intelligence Engineer

The Medpace Analytics and Business Intelligence team is growing rapidly and is focused on creating a trusted, data-driven foundation across the enterprise. We build scalable solutions leveraging data pipelines and reusable data products that ingest, transform, standardize, and serve data from operational systems for analytics, applications, and decision-making. As a Business Intelligence Intern, you will hold a highly visible role focused on modernizing data flows, improving data quality and reliability, and helping migrate fragmented data assets toward a governed single source of truth in partnership with leaders and technical teams across Medpace.

What’s in this for you?

• Work in a collaborative, fast paced, entrepreneurial, and innovative workplace.
• Build production-grade data pipelines and trusted data products used by analysts, applications, leaders, and teams across the enterprise.
• Develop your craft in Python and SQL by designing, testing, deploying, and monitoring maintainable workflows—not just one-off scripts or notebooks.
• Gain business and data domain context by partnering across Medpace to consolidate fragmented sources into scalable, governed, and reusable data solutions.

What’s involved?

We are looking for a full-time Business Intelligence Engineer to add depth to our growing team by designing and building data pipelines, shared data models, and production-ready data products in Python and SQL. This role partners closely with data engineering, analytics, operations, finance, and other technical teams to understand source systems, define trusted business logic, and deliver reliable datasets that can serve as the enterprise system of record for reporting and downstream applications.

An ideal candidate brings strong programming and data fundamentals and is excited to build reliable, maintainable data systems at scale. You enjoy tracing data from source to consumption, resolving ambiguity in definitions, designing reusable models, and implementing controls that make data accurate, discoverable, secure, and observable. You are eager to learn enterprise practices such as version control, automated testing, orchestration, deployment, lineage, monitoring, and operational ownership. We are looking for team members who are intensely curious, thrive on complex problems, and prefer durable platform solutions over short-term fixes.

What you bring to the table – and why we need you!

• Design, build, test, and maintain scalable batch and event-driven data pipelines using Python, SQL, and modern orchestration patterns.
• Ingest and integrate data from enterprise applications, databases, files, APIs, and cloud platforms into standardized data layers.
• Develop reusable, well-documented data products and dimensional or analytical models that support reporting, analytics, applications, and AI use cases.
• Help migrate legacy and duplicative data assets toward a governed single source of truth with consistent definitions, ownership, and business rules.
• Implement automated data quality checks, reconciliation controls, schema validation, lineage, logging, alerting, and performance monitoring.
• Partner with business and technical stakeholders to document source-to-target mappings, translate requirements into data contracts, and define acceptance criteria.
• Optimize pipeline performance, reliability, and cost while supporting secure access, privacy, and appropriate data governance.
• Write clean, tested, documented code; participate in peer reviews; and contribute to Git-based development, CI/CD, and release practices.
• Investigate pipeline failures and data discrepancies, perform root-cause analysis, and implement durable corrective actions.
• Use modern engineering tools, including AI-assisted development tools where appropriate, to accelerate delivery while maintaining quality, security, and human review.

• Pursuing a Bachelor's or Master's Degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Business Analytics, or a related degree.
• Proficiency in Python and SQL, with a solid foundation in data structures, debugging, modular design, and maintainable code.
• Understanding of relational databases, data warehousing, data modeling, ETL/ELT patterns, and data quality concepts.
• Familiarity with Git, automated testing, CI/CD, and software development lifecycle practices, or a strong willingness to learn.
• Strong analytical and problem-solving skills, attention to detail, and clear written and verbal communication.
• Preferred: experience with cloud data platforms and services, especially Microsoft Azure and/or Snowflake, including object storage, managed databases, compute, and role-based access.
• Preferred: exposure to data engineering and orchestration tools such as Azure Data Factory, Fabric, Databricks, dbt, Airflow, or comparable technologies.
• Preferred: familiarity with dimensional modeling, metadata, data catalogs, lineage, data contracts, observability, or master/reference data management.
• Preferred: experience with APIs, containerization, Infrastructure as Code such as Bicep, ARM, or Terraform, and deploying data workloads in cloud environments.
• Ability to work office-based in Cincinnati, OH.