Data Quality Lead

CSpring•Indianapolis, IN

About The Position

At CSpring, we believe in the power of people and data to drive real-world impact. We’re a purpose-driven consulting firm that helps organizations solve complex problems, gain insights, and achieve measurable results. Our clients span the public and private sectors, and our work — from data strategy and engineering to workforce transformation — improves lives across Indiana and beyond. We’re seeking talented professionals who are collaborative, curious, and committed to making a difference. Why You’ll Love Working Here Your work connects to real outcomes. The data you govern flows into programs that determine whether Hoosiers get the benefits they're entitled to. When the data is right, the system works — and you'll feel that every day. You'll lead something that's yours to shape. We've laid the groundwork for this initiative, but the person in this role will own its execution, refine the approach, and leave a framework that outlasts the pilot. You'll be surrounded by people who care about doing it right. The team is collaborative, experienced, and serious about quality — not just as a deliverable, but as a standard. There's room to grow, and we mean that practically. As the pilot matures and expands, so does the scope of this role. You'll have visibility with both CSpring leadership and client stakeholders, and the kind of experience that opens doors in data work for years ahead. Your perspective will shape how this program evolves. You won't be handed a rigid playbook. We want someone who will challenge assumptions, surface better approaches, and bring informed opinions to the table — then execute on them. What You’ll Do As the Data Quality Lead, you'll own the day-to-day execution of the EDW's data quality controls framework — keeping a complex, multi-layer data environment accurate, auditable, and continuously improving across a six-month pilot and beyond. Execute the DQ controls framework. You will implement data quality controls across EDW pipelines and layers, ensuring rules, logic, and monitoring are consistently applied and traceable from source to consumption. Build and maintain standardized DQ rules. You will define and document DQ rules with clear metadata, thresholds, and severity classifications — creating the kind of consistency that makes audits straightforward and remediation fast. Validate business rules with data owners. You will work directly with Data Owners and Stewards to confirm that critical data elements and business rules are accurately translated into executable controls, so the DQ framework reflects what the business actually needs. Manage the DQ rule lifecycle. You will own the full change control process for DQ rules — from creation and approval through updates and retirement — keeping documentation current and changes governed. Maintain monitoring, alerting, and exception management. You will keep a close eye on the EDW's data health in near real time, ensuring that failures surface quickly and the right people are notified with the context they need to act. Triage failures and coordinate remediation. When DQ issues arise, you will assess their downstream impact, determine urgency, and work with engineering and business teams to get to root cause and resolution — without letting problems linger or compound. Maintain failure evidence for compliance and audit. You will document DQ failure records, metrics, and audit trails in a way that satisfies regulatory expectations and makes it easy to demonstrate what happened, when, and how it was addressed. Deliver dashboards, scorecards, and operational reports. You will produce clear, timely reporting for stakeholders, translating DQ metrics into narratives that non-technical audiences can act on. Define and track metrics tied to SLAs and governance goals. You will establish the right measures of success for data quality across subject areas, track them against agreed thresholds, and escalate when trends point the wrong direction. Serve as the day-to-day DQ liaison and continuous improvement driver. You will be the connective tissue between engineering, governance, and program management — bringing teams together around shared quality standards and consistently looking for ways to make the framework smarter and more efficient.

Requirements

8+ years of experience in data quality, data governance, or data management roles supporting enterprise data warehouses
Strong working knowledge of EDW architectures, data pipelines, and multi-layer data processing environments
Hands-on experience designing and operating DQ frameworks including rules, thresholds, monitoring solutions, and exception handling
Deep fluency in core DQ dimensions: Accuracy, Completeness, Timeliness, Consistency, Integrity, Uniqueness, and Validity
Demonstrated ability to work with business stakeholders to translate operational business rules into executable data quality controls
Strong SQL skills and the ability to query, abstract, and clearly communicate what the data is telling you, both to technical teammates and non-technical decision-makers
Solid understanding of data quality and master data management concepts in practice, not just in theory
Strong written and verbal communication skills, with the ability to document processes rigorously and present findings clearly

Nice To Haves

Experience supporting Medicaid, healthcare, or government reporting environments, particularly programs with federal compliance obligations
Familiarity with cloud-based EDW platforms such as Snowflake or Azure
Experience with DQ tooling, metadata repositories, or rule engines, commercial or custom-built
Exposure to applying Generative AI or ML techniques to data quality operations, such as using prompt engineering for rule documentation, anomaly detection, or automated issue classification with a clear eye toward governance, validation, and auditability
Experience with audit, compliance, or regulatory reporting requirements
Prior experience standing up DQ governance processes or leading a pilot subject-area rollout from scratch
Proficiency with BI tools such as Tableau, Power BI, or Cognos
Working knowledge of JIRA for issue tracking, workflow management, and cross-functional collaboration
Familiarity with CMS federal reporting requirements for state Medicaid programs
Experience applying change management, incident management, or project management best practices in a data environment

Responsibilities

Execute the DQ controls framework, implementing data quality controls across EDW pipelines and layers, ensuring rules, logic, and monitoring are consistently applied and traceable from source to consumption.
Build and maintain standardized DQ rules, defining and documenting them with clear metadata, thresholds, and severity classifications.
Validate business rules with data owners, working directly with Data Owners and Stewards to confirm that critical data elements and business rules are accurately translated into executable controls.
Manage the DQ rule lifecycle, owning the full change control process for DQ rules from creation and approval through updates and retirement.
Maintain monitoring, alerting, and exception management, ensuring that failures surface quickly and the right people are notified with the context they need to act.
Triage failures and coordinate remediation, assessing downstream impact, determining urgency, and working with engineering and business teams to get to root cause and resolution.
Maintain failure evidence for compliance and audit, documenting DQ failure records, metrics, and audit trails.
Deliver dashboards, scorecards, and operational reports, translating DQ metrics into narratives for non-technical audiences.
Define and track metrics tied to SLAs and governance goals, establishing measures of success and tracking them against agreed thresholds.
Serve as the day-to-day DQ liaison and continuous improvement driver, bringing teams together around shared quality standards and looking for ways to make the framework smarter and more efficient.