Data Engineer

Job not on LinkedIn

🔥 1 hour ago

🦀 Maryland – Remote

🦀 Maryland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Magpie Health Analytics

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

🏥 Healthcare

🏛️ Government

🤖 Artificial Intelligence

Healthcare • Government • Artificial Intelligence

Magpie Health Analytics is a mission-focused small business that provides data-driven oversight, program integrity, and modernization services for U. S. federal health agencies (notably CMS and HHS). The company offers subject-matter-expert support for risk adjustment, encounter data, payment integrity (fraud/waste/abuse) analytics, RADV/CPI audit support, and policy-aligned modeling, along with cloud-native health IT and data engineering (Snowflake, AWS Glue/S3/Lambda, IaC, CI/CD). Magpie also develops AI/ML and GenAI tools—RAG, NLP, anomaly detection, explainable dashboards, and AI agents—to support audits, regulatory research, and automated analytic workflows. It operates as a GSA MAS schedule holder and SBA-registered small business and is positioned as a trusted subcontractor and technical partner for federal healthcare oversight and modernization.

📋 Description

• Design, develop, and maintain ETL/ELT pipelines using structured and semi-structured data from relational databases, flat files, APIs, and cloud data sources • Collaborate with backend and architecture teams to define data transformation flows aligned with dashboard and reporting application needs • Design and optimize data schemas to ensure performance, integrity, and compatibility with reporting requirements • Develop and maintain efficient, testable, and reusable data processing scripts using Python, SQL, and cloud-native tools • Collaborate with DevOps, analysts, and application developers to align pipelines with system architecture, storage strategy, and reporting needs • Implement data quality and validation checks and document data lineage and pipeline logic for audit and reuse • Troubleshoot performance issues in data jobs and support data pipeline operations across environments (DEV, VAL, PROD) • Contribute CI/CD workflows and automation strategies to promote rapid iteration and secure deployment of data services • Assist in developing or maintaining data documentation, including metadata, data dictionaries, and technical user guides • Stay up to date with emerging technologies, techniques, and trends to inform product development and decision-making

🎯 Requirements

• Bachelor's degree in computer science, engineering, statistics, or related field • 4+ years of experience in a data engineering, data pipeline, or ETL/ELT development role • Strong proficiency in SQL, data transformation logic, and performance tuning for large datasets • Proficiency with Python and libraries such as Pandas, PySpark, or Numpy • Experience with modern version control and CI/CD practices (e.g., GitHub Actions, Jenkins) • Understanding of distributed computing solutions for data processing (e.g., AWS Glue, AWS EMR, Apache Hadoop, Apache Spark) • Experience with data pipeline orchestration frameworks or serverless tools (e.g., AWS StepFunctions, AWS Glue Workflows, and/or AWS Lambda) • Experience developing solutions in AWS cloud environments (S3, Lambda, Aurora, SNS, CloudFormation/CDK) • Experience with Snowflake, Amazon RDS, or other cloud-native data warehouses • Familiarity with modern data transformation tools (dbt, Dataform, or equivalent) and best practices for modular, tested SQL transformations within an ELT architecture • Experience supporting healthcare data systems or CMS data environments • AWS certifications are a plus

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