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Data Analytics Jobs in Springfield, IL (NOW HIRING)

CSpring

Data Modeler

Springfield, IL · On-site +1

$54.25 - $70.25/hr

We're a purpose-driven consulting firm specializing in data strategy, data engineering, and data analytics. Our clients span the public and private sectors, and our work helps them solve complex ...

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How much do data analytics jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for data analytics in Springfield, IL is $54.26, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $61.49 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

What are the most commonly searched types of Data Analytics jobs in Springfield, IL?

The most popular types of Data Analytics jobs in Springfield, IL are:

What are popular job titles related to Data Analytics jobs in Springfield, IL?

For Data Analytics jobs in Springfield, IL, the most frequently searched job titles are:

What job categories do people searching Data Analytics jobs in Springfield, IL look for?

The top searched job categories for Data Analytics jobs in Springfield, IL are:

What cities near Springfield, IL are hiring for Data Analytics jobs?

Cities near Springfield, IL with the most Data Analytics job openings:

Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Springfield, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $112,861 per year, or $54.3 per hour.

Data Modeler

Springfield, IL • On-site, Remote

CSpring
51 - 200 employees
Learn more about CSpringexternal

$54.25 - $70.25/hr

Full-time

Posted 29 days ago

Job description

Job Type
Full-time
Description
At CSpring, we believe in the power of data to drive decisions and real-world impact. We're a purpose-driven consulting firm specializing in data strategy, data engineering, and data analytics. Our clients span the public and private sectors, and our work helps them solve complex problems, gain insights, and achieve measurable results.
We're seeking talented professionals who are collaborative, curious, and committed to making a difference that thrive at the intersection of data, technology, and business strategy. Whether you're passionate about transforming public programs, enabling executive decision-making, or modernizing legacy systems, you'll find meaningful work and purpose here.
Why You'll Love Working Here
  • Purposeful Projects - Improve systems that serve real people by delivering smarter data, streamlined processes, and strategic insight.
  • People-First Culture - We're as committed to your growth as we are to delivering high-impact solutions. You'll find support, autonomy, and community here.
  • Strategic, Hands-On Work - From data architecture and documentation to client workshops and solution delivery, you'll influence every step of the process.
  • Collaborative Trust - Our clients rely on us to listen carefully, deliver consistently, and guide wisely. We partner with integrity, curiosity, and heart.

What You'll Do
Working closely with data architects, ETL/data engineers, BI developers, DBAs, and business subject matter experts, the Senior Health Data Modeler ensures data structures are scalable, standards-compliant, well-documented, and aligned to enterprise and regulatory requirements across the Health and Human Services ecosystem.
Data Architecture & Strategy
  • Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, clients, and other key stakeholders.
  • Lead data architecture, data modeling, and data movement initiatives to enhance the data warehouse supporting analytics for Medicaid, Medicare, and Commercial healthcare data - including domains such as claims, provider, TPL, and member information subject areas.
  • Create an end-to-end vision for how logical design translates into one or more physical databases and how data flows through successive stages.
  • Document data architecture and the enterprise environment to maintain a current, accurate view that supports a single version of the truth and scales to future analytical needs.

Data Modeling & Design
  • Analyze and translate business needs into long-term solution data models; evaluate existing data systems and work with the development team to create conceptual data models and data flows.
  • Design and maintain conceptual, logical, and physical data models across staging, integration, and semantic/presentation layers.
  • Develop dimensional models (Kimball star/snowflake), normalized (OLTP/3NF), OLAP, and Data Vault patterns; implement Slowly Changing Dimensions, role-playing dimensions, dimensional hierarchies, surrogate keys, and data classification.
  • Define primary/foreign keys, indexes, partitioning, constraints, and referential integrity rules to ensure data quality and performance.
  • Produce and maintain entity-relationship diagrams (ERDs), data flow diagrams, and model documentation using Erwin or equivalent tools.

Governance, Quality & Compliance
  • Ensure data strategies and architectures are in regulatory compliance; identify where existing policies and procedures require change or where new ones are needed.
  • Oversee the mapping of data sources, data movement, interfaces, and analytics with the goal of ensuring data quality.
  • Create and maintain data model and metadata policies and procedures for functional design; maintain data dictionaries, business glossaries, and lineage documentation.
  • Support classification and protection of sensitive data (PII, PHI) in alignment with HIPAA, PHI, and SOX requirements.

Collaboration & Delivery
  • Provide technical recommendations and engage with ETL Architects, Business SMEs, and other stakeholders throughout the Solution/Data Architecture and implementation lifecycle to develop high-performance, highly scalable data solutions (data marts/warehouse, data mining, and advanced analytics).
  • Address data-related problems regarding systems integration, compatibility, and multiple-platform integration.
  • Develop and implement key components and testing criteria to guarantee the fidelity and performance of data architecture.
  • Communicate with the customer and project team in a timely manner and escalate issues and risks appropriately.

Modernization & Migration Support
  • Contribute to migration of legacy Teradata models to modern cloud platforms (Azure Synapse / Databricks Lakehouse, Snowflake).
  • Design target-state models leveraging medallion (Bronze/Silver/Gold) architecture, Delta Lake, and Parquet patterns.
  • Assess existing models for modernization opportunities, redundancy, and optimization; recommend improvements to architects.

Requirements
  • Strong problem-solving, influencing, communication, and presentation skills; self-starter.
  • 7+ years of Experience in data modeling, data strategy, and roadmap for large and complex health entities and systems; implemented large-scale, end-to-end Data Management & Analytics solutions for more than one large client.
  • 5+ years of Strong knowledge of regulatory security requirements regarding HIPAA, PHI, PII, and other healthcare data security standards.
  • 5+ years of Experience with Erwin Data Model (or comparable tools such as ER/Studio, SQL Developer Data Modeler).
  • 5+ years of strong healthcare domain knowledge of Medicaid, Medicare, and Commercial healthcare data sets.
  • Expertise with normalized OLTP, OLAP, MDM, and dimensional modeling techniques - star schemas, slowly changing dimensions, role-playing dimensions, dimensional hierarchies, and data classification.
  • 5+ years of Expert-level SQL skills with direct experience writing complex analytic queries, stored procedures, DDL, DML, and DCL; thorough knowledge of query optimization and the ability to write to ANSI standards and review others' code.
  • 5+ years of experience in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, MDM, Data Archival, and Data Migration strategies using appropriate tools.
  • Demonstrated ability to work in a fast-paced, changing environment with short deadlines, interruptions, and multiple concurrent tasks/projects.
  • Ability to work independently with strong planning, strategy, estimation, and scheduling skills.

Preferred Qualifications
  • Experience with Microsoft Azure cloud infrastructure and services (Azure Data Lake Storage, Azure Data Factory, Purview, Azure Maps, etc.).
  • Experience with Snowflake DBMS, including object design and performance tuning.
  • Experience with Power BI or Tableau.
  • Experience supporting State Medicaid EDW, MMIS, or federal reporting programs (T-MSIS, PERM, MARS, Quality of Care).
  • Exposure to Teradata Vantage 20 and modernization of Teradata workloads onto cloud platforms.
  • Familiarity with Delta Lake / lakehouse architecture and Microsoft Fabric.
  • Exposure to AI/ML and GenAI tools (e.g., GitHub Copilot, Microsoft 365 Copilot, Snowflake Cortex) for accelerating modeling, documentation, and metadata enrichment.
  • Hands-on experience with ETL tools (e.g., Informatica, Azure Data Factory).
  • Hands-on experience with BI tools and reporting software.
  • Experience with a scripting language used for analytics such as Python or R.

Come Build With Us
At CSpring, we unlock the potential of people and data. If you're ready to lead meaningful projects, collaborate with passionate teams, and grow your career in a people-first consulting environment-apply today!

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