Description

You will build and maintain enterprise-scale data pipelines and batch processing frameworks to support application engineering and analytics.

Responsibilities

• Design and implement scalable data pipelines, ingestion, transformation, and data quality features.
• Collaborate with Data Architects and Business Analysts to build data models for improved reliability and interpretability.
• Develop and maintain data export solutions for efficient transfer to external systems and platforms.
• Write unit, integration, and functional tests for new features and support production jobs to mitigate issues.
• Contribute to design documents, technology assessments, Proof of Concepts, PR reviews, and technical standards.

Required Skills

• 5+ years of experience as a Data Engineer building enterprise data solutions.
• 3+ years of cloud experience with Azure, AWS, or GCP.
• Expertise in Microsoft SQL Server or other relational databases, including stored procedures, triggers, and performance tuning.
• Strong experience with the Microsoft ETL stack, including SSIS and Azure Data Factory.
• Proficiency in Python or another programming language.
• Hands-on experience with Big Data technologies such as Spark or Databricks.
• Proven track record of building scalable, fault-tolerant data pipelines and data lakes for high-speed querying.
• Strong SQL skills and experience with data modeling.

Preferred Skills

• Experience with healthcare information exchange standards: HL7, X12 EDI, or FHIR.
• Knowledge of creating RESTful APIs.
• Experience building dashboards and visualizations using Power BI.

Key Skills

Education

Any Gradute