Data Engineer

Description:

Syndeo's Data Science practice combines clinical and financial data into a single, automated view of the pathology business, a capability that sets our platform apart. We are looking for a Data Engineer to build and operate the pipelines that make this possible, pulling structured and unstructured data out of Artyfica's core services (LAB, RCM, CRM) and the iConnect interoperability engine, and turning it into governed, analytics-ready datasets. This role is foundational to the Data Science layer of Artyfica, working closely with the Data Analyst, Data Scientists, Product Owner, and Scrum Master to keep the ecosystem's intelligence layer fast, trustworthy, and scalable.

Responsibilities of the job include:

Design, build, and maintain ETL/ELT pipelines that ingest data from Artyfica's core services (LAB, RCM, CRM) and the iConnect interoperability engine
Build and evolve data warehouse and data lake models that unify clinical and financial data for Data Science consumption
Establish and enforce data quality, integrity, lineage, and governance standards across all pipelines
Partner with Data Analysts and Data Scientists to expose clean, curated, well-documented datasets for reporting and modeling
Optimize pipeline performance and scalability as data volume and organizational onboarding grows
Implement monitoring and alerting to proactively catch pipeline failures or data quality issues
Collaborate with the Software Development team to align data schemas with Artyfica's service-oriented architecture
Maintain data catalogs and documentation for all pipelines and datasets
Support ingestion of HL7, FHIR, X12, and BAI2 (BTRS) data structures arriving through iConnect

Required skills:

Proficient in Python and/or Java for data engineering work
Strong SQL skills and hands-on experience with relational databases (Postgres preferred)
Experience with ETL/ELT design and orchestration tools (e.g., Airflow or equivalent)
Solid understanding of data warehousing and data lake concepts and dimensional modeling
Working knowledge of data governance principles and secure handling of protected health information (PHI)
Proficient with Git and version control workflows
Comfortable operating within Agile Scrum and Kanban practices
Logical thinker with strong analytical and problem-solving skills
Written and verbal communication skills in both Spanish and English

Desired skills:

Experience with healthcare interoperability standards: HL7, FHIR, X12, BAI2
Exposure to cloud or analytics platforms such as Snowflake, ClickHouse, or Trino
Prior experience integrating financial and clinical data domains
Familiarity with streaming or event-driven pipelines (e.g., Kafka)
Experience with Docker and containerized data services

Qualifications and training:

Bachelor's Degree in Computer Science, Data Engineering, or a related field
3+ years of experience in data engineering
Experience with healthcare, RCM, or laboratory data preferred

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