Gravity IT Resourcing
Data Engineer
Philadelphia, Pennsylvania
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Job Title: Senior Data Engineer (Data Strategy & Project Leadership)
Job Type: Full-Time
Job Summary
The Senior Data Engineer will play a pivotal role in designing and implementing data architecture, building data pipelines, and ensuring data infrastructure supports key business and clinical initiatives. This position will focus on developing robust data engineering solutions, optimizing data workflows, and driving data governance to support data-driven decision-making across the organization.
Key Responsibilities
Data Engineering & Infrastructure
- Lead and execute complex data engineering projects, from design to implementation, ensuring alignment with business and clinical objectives.
- Architect, build, and optimize data pipelines that integrate various data sources into a centralized data platform, ensuring efficient data processing and storage.
- Develop scalable data solutions to handle large datasets and real-time data flows, improving the organization’s data accessibility and processing capabilities.
- Collaborate with data scientists, analysts, and business stakeholders to design and maintain data models that meet analytical and operational needs.
- Oversee the management and optimization of cloud-based data environments (e.g., Snowflake, Databricks) to ensure performance, scalability, and cost efficiency.
Data Governance & Quality Assurance
- Implement and enforce data governance policies and standards to ensure the integrity, quality, and consistency of data across the organization.
- Collaborate with IT and compliance teams to develop and maintain data security and privacy measures, ensuring compliance with regulatory standards (e.g., HIPAA).
- Conduct data audits and validation processes to identify and resolve discrepancies, ensuring high-quality and reliable data is available for business use.
Project Leadership & Collaboration
- Work closely with the executive team and cross-functional leaders (IT, Operations, Finance, Development) to define and prioritize data infrastructure projects and initiatives.
- Oversee the execution of data engineering projects, coordinating resources, timelines, and deliverables to meet business objectives.
- Act as a key advisor on data architecture and engineering best practices, providing leadership and guidance to the broader team.
- Foster collaboration between engineering, analytics, and business teams to ensure seamless data workflows and efficient data integration across the organization.
EMR Data Strategy & Integration
- Lead the integration of EMR/PM data systems (e.g., eCW, MedENT, ModMED, AllScript) into the organization’s data infrastructure, ensuring that clinical and operational data flows smoothly for analysis and reporting.
- Collaborate with clinical teams to design data pipelines that facilitate the extraction, transformation, and loading (ETL) of EMR/PM data for advanced analytics and reporting.
- Ensure that clinical data systems adhere to best practices for data quality, integration, and security.
Qualifications
Education & Experience
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
- 5+ years of experience in data engineering, with a strong background in designing and implementing data systems and data pipelines.
- Experience working with healthcare data systems (e.g., EMR/PM data) is preferred.
Skills & Competencies
- Advanced expertise in SQL, data modeling, and building data pipelines.
- Proficiency in cloud-based data platforms (e.g., Snowflake, Databricks) and managing multi-cluster architecture, secure data sharing, and compute/storage separation.
- Strong experience with ETL tools and technologies (e.g., Apache Airflow, dbt, Talend).
- Proficient in data processing and programming languages like Python, Scala, or Java, and familiar with big data frameworks (e.g., Hadoop, Spark).
- Deep understanding of data governance, data security, and compliance standards.
- Strong problem-solving skills, with the ability to design scalable and efficient data architectures that support complex workflows.
- Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Proven leadership ability to manage multiple projects and collaborate with cross-functional teams.
Preferred Skills
- Experience with cloud services (e.g., Azure, AWS) and containerized data solutions (e.g., Docker, Kubernetes).
- Familiarity with healthcare IT standards (e.g., HL7, FHIR).
- Knowledge of data privacy and compliance regulations such as HIPAA.