Overview
The Data Integration Specialist is responsible for establishing, maintaining, and improving Consensio Health’s client data feeds, data specifications, and data pipeline infrastructure. This role supports all data needed for medical billing operations, analytics platforms, and other internal systems. The position coordinates with clients, hospital IT teams, and other vendors to establish new data feeds, monitor and validate existing feeds, and troubleshoot any data-related issues.
Beyond ongoing feed work, the Data Integration Specialist will work closely with the development team to build and maintain a new AWS-based data lake and ETL pipeline to port existing processes to more modern architecture, and will be involved in other larger data-related projects over time.
The position reports to the Director of Technology but requires a high level of independence. The role is expected to manage their own day-to-day priorities while working towards longer-term goals.
Duties
- Establish new client data feeds with hospital IT teams, vendors, or other external technical contacts.
- Communicate data requirements through email, ticketing systems, and occasional client or vendor calls.
- Coordinate secure data transfer setups, including SFTP, HL7, API-based feeds, VPN connections, IP whitelisting, etc.
- Review incoming raw data to confirm required fields, formats, identifiers, mappings, etc are present and usable.
- Build and maintain scripts and automated tools to monitor feed delivery, data completeness, and data quality.
- Investigate feed failures, missing files, malformed data, incorrect filtering, junk data, and other feed-related issues.
- Review logs, test connections, inspect raw source data, and coordinate with source IT teams to restore failed or incomplete feeds.
- Maintain documentation for feed configurations, source systems, field mappings, validation processes, contacts, etc.
- Maintain and improve Consensio Health’s internal data specification for billing, quality analytics, and other application needs.
- Work with the Consensio Health technology team to build and maintain AWS-based data infrastructure.
- Develop ETL processes that extract, transform, validate, and load data from client systems, billing systems, or other sources.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, or a related field.
- Strong experience working with structured data formats such as CSV, RPT, fixed-width files, JSON, XML, or HL7 messages.
- Strong SQL experience with relational databases such as SQL Server, PostgreSQL, or MySQL.
- Programming experience writing scripts to process, validate, transform, or reconcile data.
- Familiarity with secure data transfer methods such as SFTP, VPN-based transfers, SSH keys, IP whitelisting, APIs, and HL7 interfaces.
- Experience with AWS data services such as S3, Glue, Lambda, Step Functions, RDS.
- Familiarity with data lakes, data warehouses, ETL, and data modeling preferred.
- Understanding of HIPAA, PHI handling, healthcare privacy, or secure data exchange practices preferred.
- Experience working with healthcare data preferred.
- Ability to work independently, manage long-term priorities, and communicate clearly with technical and non-technical stakeholders.
Preferred Skills
- Data Engineering Skills: SQL, ETL design, data mapping/normalization, data monitoring, and reconciliation.
- Programming Skills: Python, C#, or another language used for scripting/data transformation.
- Data Integration Skills: SFTP, HL7, APIs, VPN, SSH.
- AWS Skills: S3, Glue, Lambda, Step Functions, EventBridge, RDS.
- Documentation Skills: Data specifications, field mappings, feed setup guides, technical onboarding notes.
- Soft Skills: Attention to detail, strong organizational and prioritization skills, effective communication and teamwork, analytical and critical thinking abilities.
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Health insurance
- Health savings account
- Paid time off
- Retirement plan
- Vision insurance
Application Question(s):
- Bachelor’s degree in Computer Science, Data Engineering, or a related field?
Work Location: Remote
