Intern Adaptive Data Operations Specialist Jobs (NOW HIRING)

Vida Health is looking for a Senior Data Operations Specialist to join our Client Success TechOps team. You will be the senior technical and operational point of contact for data exchange between Vida and our clients and vendors — owning the full lifecycle of inbound and outbound file integrations, from initial spec negotiation through ongoing quality assurance and process improvement.

Vida ingests a high volume of inbound feeds including eligibility records, medical and pharmacy claims, PAs, rosters, and vendor transitions. These datasets are sent by different carriers on varying cadences and quality standards. This role owns making that heterogeneous inflow reliable, mapped correctly, and QA’d before it moves downstream.

You will work closely with a Data Management Associate, client technical teams, and Vida's product and engineering teams to ensure data flows reliably, accurately, and at scale. A key part of your work will happen in Vida's Client Command Center: Configure platform, and your insights will directly shape how we standardize and evolve our data exchange practices

• Own ingestion of inbound feeds including eligibility records, medical and pharmacy claims, PAs, rosters, and vendor transitions. These datasets are sent by different carriers on varying cadences and quality standards. 
• Serve as Vida's senior technical point of contact for data exchange negotiations with clients and vendors, including SFTP/file transfer specifications, connection setup, and protocol agreements.
• Define and communicate expectations for inbound and outbound file exchanges- formats, schedules, error handling, and escalation paths.
• Lead onboarding of new client data feeds from kickoff through steady-state, ensuring a smooth and well-documented handoff.
• Own the quality of data received from clients- you are the accountable party for ensuring inbound files are complete, accurate, timely, and spec-compliant.
• Establish and enforce data quality standards and acceptance criteria for all inbound feeds; reject or escalate non-conforming data rather than letting it flow downstream.
• Proactively detect quality degradation trends before they become business-impacting issues, and drive resolution directly with client technical teams.
• Partner with engineering and analytics to understand how upstream data quality affects downstream member outcomes, billing accuracy, and client reporting- and use that context to prioritize where quality improvements matter most.
• Maintain clear, accurate documentation of all active integrations, specs, data dictionaries, and known quality issues.
• Monitor and manage ongoing inbound and outbound file exchange workflows, triaging issues and driving resolution with internal and external stakeholders.
• Maintain SLA awareness across client feeds and escalate proactively when at risk.
• Understand and troubleshoot ingestion pipeline behavior (parse → validate → transform → load); partner with engineering on root-cause analysis of failures, distinguishing source-data problems from pipeline problems.
• Observe existing workflows and proactively identify opportunities to improve efficiency, reduce manual touchpoints, and increase data quality.
• Partner with the product team to translate operational pain points into platform enhancements within Client Command Center: Configure.
• Identify and drive standardization opportunities across clients and vendors- reducing one-off configurations and building toward scalable, repeatable patterns.
• Work closely with the Data Management Associate to divide coverage, share knowledge, and build team capability.
• Collaborate with engineering and product on integration specs and platform tooling.
• Partner with Client Success Managers to ensure data operations align with client commitments and SLAs, which may include attendance at client-facing meetings.

• Bachelors degree preferred or equivalent applicable experience. 
• 5+ years of experience in data operations, data integration, or technical client success- ideally in a healthcare SaaS environment.
• Hands-on experience with SFTP/managed file transfer (MFT)- setup, troubleshooting, and spec documentation.
• Strong working knowledge of common healthcare data formats (e.g., EDI 834/837, HL7, FHIR, delimited flat files) with emphasis on: medical claims, eligibility files, plus pharmacy claims (NCPDP Post Adjudication), prior authorizations, rosters, vendor-transition files, and delimited flat files.
• Experience mapping vendor data files to a defined target schema/spec.
• Experience profiling, validating, and reconciling incoming data (data QA, error handling). Quality as a concrete competency, not just a mindset.
• Working knowledge of data ingestion pipelines that includes how files are parsed, validated, transformed, and loaded; ability to debug pipeline failures and distinguish source-data problems from pipeline problems.
• Basic SQL skills and/or experience with other coding languages, as well as experience with GitHub or a similar platform to write, test, and debug code.
• Experience handling many concurrent feeds with non-standard formats and varying quality across multiple carriers and cadences.
• Demonstrated ability to communicate technical requirements clearly to both technical and non-technical client stakeholders.
• A strong bias toward quality ownership- you don't pass bad data downstream and ask questions later.
• Experience identifying and leading process improvement initiatives- you don't wait to be asked.
• Experience with AI tools and how they can be used to evolve and improve workflows.
• Comfortable working across product, engineering, and client-facing teams simultaneously.

• Experience working in or alongside a digital health/health benefits platform.
• Familiarity with data configuration or admin tooling (experience with platforms like Client Command Center a plus).
• Experience with Google Cloud Storage (GCS/BigQuery).
• Familiarity with clinical data standards (HL7, FHIR) — useful but secondary to the claims focus of this role.
• Experience building toward vendor/client data standardization across a portfolio.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.