Engineer Jobs in Maplewood, NJ

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1mo ago

Data Analytics Engineer

StationMD Maplewood, NJ

Maplewood, NJ

1mo ago Closed

$110k - $115k/yr Full time Analytics Big Data Business Analytics

This position is no longer accepting applications (closed Jul 24, 2026).

Job Description

This onsite role in Maplewood, New Jersey offers a competitive annual compensation between USD 110,000 and 115,000. You will join a telehealth organization focused on serving individuals with intellectual and developmental disabilities (I/DD). StationMD provides 24/7 telemedicine access with board-certified clinicians and specialized psychiatry services, aiming to deliver high quality care while reducing unnecessary medical costs. You’ll be part of a collaborative Data & Analytics team that emphasizes reliable data assets and governance to enable future analytics and operational insights.

Responsibilities

Design, build, and maintain data ingestion and transformation pipelines across healthcare, operational, contract, patient, roster, and enterprise source systems.
Support the enterprise analytics platform foundation, including raw, standardized, and curated data layers.
Create reusable ingestion and transformation patterns using Snowflake, SQL, and related data engineering tools.
Partner with internal teams and consulting partners to implement metadata-driven pipeline controls, process logging, audit columns, and batch tracking.
Implement data quality checks to verify 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, leadership, financial, clinical operations, and self-service analytics.
Collaborate 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 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 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.
Leverage data modeling approaches such as star and dimensional models, slowly changing dimensions, or data vault concepts as appropriate.

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, BI engineering, data warehousing, or ETL/ELT development.
Strong SQL skills with experience building, testing, and optimizing data transformations.
Experience 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

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