Data Analytics Engineer

Data Analytics Engineer role at StationMD in Maplewood, NJ (onsite), with a salary range of USD 110,000 to 115,000 per year to support the buildout of StationMD’s enterprise data analytics platform.

Responsibilities

• Construct and sustain ETL/ELT pipelines to ingest and transform data from healthcare, operational, contract, patient, roster, and enterprise source systems
• Assist in establishing the analytics platform foundation, including raw, standardized, and curated data layers
• Create reusable ingestion and transformation patterns using Snowflake, SQL, and related data engineering tools
• Collaborate with internal teams 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, de-duplication, and source to target reconciliation
• Help develop and maintain control tables, error logging, reject handling, monitoring, and recovery workflows 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
• Partner with business stakeholders to clarify data definitions, business rules, source system nuances, and reporting requirements
• Contribute to data governance efforts, 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
• Engage 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 equivalent version control to manage analytics code, promote changes across environments, and support peer reviews
• Collaborate with reporting and analytics users to ensure curated datasets are reliable, understandable, and fit for business use
• Experience with data modeling techniques such as star schema, dimensional modeling, slowly changing dimensions, or data vault concepts

Requirements

• Bachelor’s degree in Computer Science, Statistics, Data Science, or a 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

Technologies

• Snowflake, SQL, Azure SQL, Databricks, Redshift, PostgreSQL
• Git, dbt, Airflow, Azure Data Factory, Fivetran, Matillion, Informatica, SSIS
• Python, Snowpark
• Qlik, Power BI, Tableau, Sigma
• Salesforce, Salesforce Health Cloud, Salesforce Data Cloud