Data Analytics Engineer

StationMD is seeking a Data Analytics Engineer to support the buildout of our enterprise data analytics platform. This role will be a core member of the Data & Analytics team and will help design, build, and operate reliable data pipelines, analytics data models, and data quality processes across key business domains.

The initial focus of this role will be supporting the execution of StationMD's data strategy, including the ingestion and transformation of core data domain into a trusted analytics platform. This role will work closely with internal data team members, business stakeholders, technology partners, and external consulting partners to build a scalable foundation for future analytics, reporting, and operational insights.

The ideal candidate is highly skilled in SQL, understands modern cloud data platform patterns, and is comfortable working across data ingestion, transformation, data quality, documentation, and production support. This position bridges analytics engineering and data platform delivery by helping convert raw source data into governed, reusable, and trusted analytics assets., * Build and maintain ETL/ELT pipelines to ingest and transform data from healthcare, operational, contract, patient, roster, and enterprise source systems

• Support the implementation of StationMD's enterprise analytics platform foundation, including raw, standardized, and curated data layers
• Develop reusable ingestion and transformation patterns using Snowflake, SQL, and related data engineering tools
• Partner with internal team members and consulting partners to implement metadata-driven pipeline controls, process logging, audit columns, and batch tracking
• Implement data quality checks to validate completeness, accuracy, timeliness, duplicate handling, and source-to-target reconciliation
• Help build and maintain control tables, error logging, reject handling, monitoring, and recovery processes for data pipelines
• Support file-based ingestion patterns, including source file tracking, raw file preservation, archive/quarantine processes, and reprocessing controls
• Develop analytics-ready data models to support operational reporting, leadership reporting, financial analysis, clinical operations, and future self-service analytics
• Work with business stakeholders to understand data definitions, business rules, source system nuances, and reporting needs
• Support data governance practices, including data lineage, metadata documentation, access controls, data stewardship, and metric standardization
• Apply security and privacy best practices for sensitive healthcare data, including PHI/PII handling, data encryption, role-based access, and auditability
• Participate in testing, validation, troubleshooting, and production support for data pipelines and analytics datasets
• Create and maintain technical documentation, data dictionaries, runbooks, and support procedures
• Use Git or similar version control practices to manage analytics code, promote changes across environments, and support peer review
• Collaborate with reporting and analytics users to ensure curated datasets are reliable, understandable, and fit for business consumption
• Experience with data modeling techniques such as star schema, dimensional modeling, slowly changing dimensions, or data vault concepts

Do you have experience in Version control systems?, Do you have a Bachelor's degree?, Education/Certification

• Bachelor's degree in Computer Science, Statistics, Data Science, or related field
• Advanced degree preferred., * 3+ years of experience in data engineering, analytics engineering, business intelligence engineering, data warehousing, or ETL/ELT development
• Strong SQL skills with experience building, testing, and optimizing data transformations
• Experience working with Snowflake or a comparable cloud data platform such as Azure SQL, Databricks, Redshift, or PostgreSQL
• Experience designing or supporting ETL/ELT pipelines using batch, incremental, or file-based ingestion patterns
• Understanding of modern data platform concepts, including raw/bronze, standardized/silver, curated/gold, dimensional modeling, and analytics-ready datasets
• Experience implementing data quality checks, reconciliation logic, audit columns, and error handling
• Ability to troubleshoot production data issues, identify root causes, and support pipeline recovery
• Experience documenting data pipelines, data definitions, business rules, and technical support procedures
• Experience using Git or similar version control tools
• Strong communication skills with the ability to work with technical teams, business stakeholders, and external partners, * Hands-on experience with Snowflake features such as stages, file formats, streams, tasks, dynamic tables, Snowpark, role-based access, and query performance optimization
• Familiarity with PHI/PII handling, data encryption, minimal access - least privilege data access, data anonymization
• Experience building analytics datasets for BI tools such as Qlik, Power BI, Tableau, Sigma, or similar platforms
• Familiarity with Salesforce, Salesforce Health Cloud, Salesforce Data Cloud, or CRM-related data integrations
• Experience with Python for data automation, validation, scripting, or pipeline support
• Exposure to CI/CD practices for data engineering or analytics engineering
• Experience with dbt, Airflow, Azure Data Factory, Fivetran, Matillion, Informatica, SSIS, or similar data pipeline/orchestration tools