Senior Data Reporting Engineer

Location: Deerfield, IL – Hybrid (4 days onsite / 1 day remote)

Duration & Type: 6-month contract with potential for extension or full-time conversion – Mon-Fri, 8:00 AM–5:00 PM CST

Compensation: Competitive hourly W2 rate ($51–$53.50/hour), access to healthcare & dental insurance plan of choice

About the role

We are seeking a Senior Data Reporting Engineer to design, develop, automate, and optimize scalable data solutions supporting enterprise reporting, analytics, research, and large-scale operational processes. This role combines strong data engineering and development capabilities with the analytical skills necessary to transform complex datasets into meaningful business insights. The ideal candidate will bring approximately 5+ years of experience in data/reporting engineering, analytics engineering, data development, or a related technical field, although candidates with fewer years may be considered when they demonstrate the appropriate technical depth.

Core technical requirements include strong hands-on experience with Databricks, SQL, CI/CD pipelines, and development/DevOps practices. Experience working with comparable enterprise technologies and environments such as Snowflake, Teradata, SaaS platforms, Azure, or other cloud-based data platforms is also valuable. Depending on team alignment, this individual may lean more heavily toward either data engineering and operationalization or analytics, reporting, research, and modeling.

Experience within healthcare, pharmacy, patient, or related analytical environments is particularly valuable.

Responsibilities

• Design, develop, maintain, and optimize scalable data solutions supporting enterprise reporting, analytics, research, and operational business processes.
• Build and support robust data pipelines that ingest, transform, process, and deliver large volumes of data from internal and external sources.
• Develop and optimize complex SQL queries, data transformations, and processing workflows.
• Work extensively within Databricks and cloud-based data environments to develop scalable data processing and analytical solutions.
• Support the migration and modernization of existing data processes from legacy or enterprise environments such as Teradata and SaaS platforms into Azure Databricks.
• Develop automated processes supporting large-scale operational datasets, enrollment data, external files, reporting feeds, and other recurring business processes.
• Participate extensively in CI/CD, DevOps, deployment, testing, version control, and production support processes for enterprise data solutions.
• Build reliable, automated data processes with a strong focus on scalability, performance, maintainability, and operational stability.
• Develop and maintain daily, weekly, and recurring reporting processes and the underlying pipelines required to support them.
• Analyze large and complex datasets to identify trends, patterns, anomalies, volume changes, and underlying business issues.
• Investigate changes in business performance or operational activity and determine the data-driven factors contributing to those changes.
• Develop reporting datasets, analytical frameworks, KPIs, quality measures, and other data products that support business decision-making.
• Support analytical and research initiatives involving areas such as pharmacy practice, patient and medication quality, service programs, targeting, and public health-related analysis.
• Apply statistical, analytical, or modeling techniques when appropriate to identify patterns, develop insights, and support business or operational strategies.
• Help translate analytical findings, research, and models into scalable data solutions that can ultimately be operationalized within enterprise engineering environments.
• Partner with data engineers, analysts, data scientists, developers, and business stakeholders to translate complex business requirements into effective technical and analytical solutions.
• Maintain strong standards for data quality, validation, governance, security, monitoring, and documentation.
• Troubleshoot data pipeline, processing, reporting, and production issues and identify appropriate long-term solutions.
• Communicate technical and analytical findings clearly to both technical and non-technical stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, Data Science, Engineering, or a related quantitative or technical discipline.
• Approximately 5+ years of experience in data engineering, reporting engineering, analytics engineering, data development, business intelligence, or a related field; flexibility may be considered for candidates demonstrating strong technical expertise.
• Strong hands-on experience with Databricks in an enterprise data environment.
• Advanced proficiency with SQL and relational data concepts.
• Hands-on experience developing, maintaining, and troubleshooting production-level data pipelines.
• Strong understanding of CI/CD pipelines, development practices, and DevOps methodologies.
• Experience developing automated and scalable data processing solutions.
• Experience working with large, complex datasets across multiple data sources and environments.
• Experience with cloud-based data platforms and modern enterprise data architectures.
• Strong analytical and troubleshooting skills with the ability to investigate data, identify patterns, and determine the root causes behind technical or business issues.
• Ability to balance technical engineering requirements with broader reporting, analytics, and business objectives.
• Strong communication skills with the ability to collaborate effectively across engineering, analytics, data science, and business teams.

Preferred Qualifications

• Experience working within Microsoft Azure and Azure Databricks environments.
• Experience with Teradata, Snowflake, SaaS data platforms, Apache Spark, or comparable enterprise data technologies.
• Experience migrating or modernizing data pipelines and processing workflows from legacy environments into cloud-based platforms.
• Experience with Python or another programming language used for data processing, analytics, and automation.
• Experience supporting healthcare, pharmacy, medical, patient, claims, or related healthcare datasets.
• Background in healthcare analytics, pharmacy analytics, health informatics, or other analytically intensive healthcare environments.
• Experience supporting large-scale operational data processing, enrollment files, external data feeds, or automated batch processes.
• Experience with statistical analysis, analytical modeling, targeting, research, or advanced analytics.
• Experience developing KPIs, quality metrics, operational reporting, or analytical frameworks.
• Experience with Git, Azure DevOps, or comparable source-control and deployment technologies.
• Experience translating analytical findings or models into scalable, production-ready data solutions.

Benefits

• Access to healthcare & dental insurance plan of choice