Senior Data Enablement and Quality Analyst

CVS Health•Woonsocket, RI

2d•$66,330 - $145,860•Hybrid

About The Position

CVS Health is building a world-class analytics organization within the Procurement Center of Excellence (CoE), and we are looking for a Manager, Data Enablement & Quality to help lay the foundation it runs on. This is a technical role for someone who thinks rigorously about data and can communicate clearly with business stakeholders. You will be responsible for ensuring procurement has access to the right data, structured correctly, and delivered in a way that analysts and business users can actually trust and use. Day to day, that means working with the enterprise Data Portal and IT partners to assess available data, close gaps, and build governed BigQuery datasets that serve as the single source of truth for procurement reporting. Over time, the role will grow into a broader data stewardship function, including data profiling, quality program development, and driving master data standards across procurement domains. Strong candidates will be hands-on technically, comfortable working across IT and business teams, and motivated by building something that others will rely on. Note: This is a hybrid role requiring 2 days per week minimum (Tuesday & Wednesday) at either the Hartford or 1 CVS Drive Offices.

Requirements

5 or more years of experience in a data, analytics engineering, or business intelligence role with a strong SQL and data modeling focus
Advanced SQL skills, including complex data modeling, transformation logic, and building layered views and datasets in a cloud data warehouse
Hands-on experience with Google BigQuery or a comparable cloud platform such as Snowflake or Redshift
Experience building and publishing data sources in Tableau Server, including row-level security and semantic layer configuration
Working knowledge of data quality principles, governance concepts, and what it takes to produce a dataset others can trust
Ability to communicate technical work clearly to non-technical business stakeholders
Comfortable driving work forward independently and bringing structure to problems that are not yet well-defined

Nice To Haves

Familiarity with GCP services including Google Cloud Storage and Dataproc
Experience with Python for data validation, automation, or lightweight processing tasks
Familiarity with Dataiku or similar tools used for ad hoc analysis against structured datasets
Experience with data transformation or orchestration tools such as dbt
Experience with SAP Ariba, SAP S/4HANA, or ServiceNow as data sources
Experience working with enterprise data catalog or data portal tools
Familiarity with master data management concepts and data profiling techniques
Background in procurement, supply chain, finance operations, or a similarly complex enterprise domain is a plus but not required

Responsibilities

Evaluate procurement data needs against assets available in the enterprise Data Portal, assessing domain coverage, field definitions, and data quality scores to determine fitness for use.
Partner with IT and system owners to extract and land the required data in GCP, ensuring it is properly structured and documented for use in BigQuery.
Build and maintain BigQuery tables, views, and data models that transform source data into clean, standardized gold-layer datasets for procurement reporting and analytics.
Determine the right delivery mechanism for each dataset: publish as a data source in Tableau Server with row-level security and semantic modeling where a dashboard is needed, or document as a BigQuery table or view for consumption via Python, Dataiku, or other tools where one is not.
Ensure every dataset the CoE produces is fully documented, including field definitions, business logic, data lineage, refresh cadence, and known limitations.
Work with business SMEs to validate that data definitions and logic are correct, and obtain sign-off before datasets are published for broad use.
Drive consolidation toward a single source of truth within each procurement data domain. Where multiple reports or datasets exist covering the same business question with inconsistent logic, this role is responsible for resolving that fragmentation into one authoritative, well-defined dataset.
Over time, develop repeatable processes for how data products are defined, reviewed, approved, and maintained as the CoE matures.
Assess, clean, and prepare procurement data as part of building the first iteration of gold-layer datasets, identifying and resolving issues with completeness, consistency, and structure.
Use quality scores and metadata from the Data Portal as a baseline, and document additional quality findings surfaced during the build process.
Implement data profiling practices to identify where quality breaks down across procurement processes, and distinguish between issues that can be fixed in the data layer versus those that require upstream process changes.
Partner with IT, system owners, and business stakeholders to advocate for and implement durable fixes at the source rather than building around problems downstream.
Translate requirements from procurement stakeholders and CoE analysts into technical data solutions, and communicate clearly about what the data can and cannot support.
Proactively surface data gaps, quality issues, and coverage limitations to business partners and CoE leadership, and help drive prioritization decisions around how to address them.
Serve as a technical resource for CoE analysts acting as data product owners, ensuring the datasets they depend on are reliable, well-documented, and understood.