Data Engineer TMC Job McLean area,Virginia USA,IT/Tech

Position: Data Engineer TMC011005

Job Description

The TMCI Data Quality Group is seeking a talented and experienced Data Engineer to join our dedicated team. As a Healthcare IT Data Engineer, you will play a pivotal role in designing, developing, and maintaining data pipelines, databases, and analytics solutions that support data-driven decision-making and patient care improvements in the healthcare industry. This position requires a thorough understanding of modern data warehousing concepts like data lakes and data lake houses.

The ideal candidate will be familiar with data modeling techniques such as Data Vault and Star Schema, and should be proficient in building, testing, and implementing data pipelines. They should also have experience with products like DBT and understand Directed Acyclic Graphs (DAGs). This role is within a government context requiring U.S. citizenship, a college degree, and eligibility to obtain a security clearance.

Key Responsibilities

Data Integration and ETL: Design and build data integration pipelines for collecting, cleansing, and transforming healthcare data from various sources, including electronic health records (EHR), medical devices, and clinical systems.

Database Management: Develop and maintain healthcare databases, ensuring data accuracy, reliability, and compliance with industry standards and regulations, including HIPAA.

Data Architecture: Collaborate with data scientists, analysts, and healthcare professionals to design data architectures that enable advanced analytics, machine learning, and reporting.

Optimization and Performance: Continuously optimize data processing and storage systems for enhanced performance and scalability, enabling real-time data access and analytics.

Data Security and Compliance: Implement robust data security measures to protect sensitive patient information, adhere to healthcare compliance standards, and perform routine audits.

Data Warehousing: Develop and maintain data warehousing solutions for efficient storage, retrieval, and analysis of large healthcare datasets.

Data Documentation: Create and maintain documentation for data models, data dictionaries, and data lineage to support transparency and data governance.

Collaboration: Collaborate with cross-functional teams, including data scientists, analysts, clinicians, and IT professionals, to ensure data infrastructure meets healthcare data requirements.

Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
U.S. Citizenship required and the ability to obtain a DOD clearance.
Must reside in Virginia, Maryland, or DC Metro Area.
Eligibility for Government security clearance.
Proven experience as a Data Engineer in the healthcare industry, or relevant role in the field.
Ability to communicate complex technical issues clearly in English.
Proficiency in ETL tools, data integration platforms, and database management systems (e.g., SQL, No

SQL).
Strong knowledge of healthcare data standards, terminologies (ICD-10, SNOMED), and electronic health records (EHR) systems.
Understanding of healthcare compliance and regulations, including HIPAA.
Expertise in data modeling and data architecture.
Understanding of modern data warehousing concepts and experience with environments such as Red Shift.
Proficiency in Python and SQL, with exposure to PySpark.
Familiarity with Python packages like Pandas, Spark.sql, and DuckDB.
Knowledge in DBT and understanding of DAGs.
Some experience in data modeling techniques, including Data Vault and Star Schema.
Prior experience in building, testing, and implementing data pipelines.
Experience with machine learning pipelines is a plus, but not required.
Excellent problem-solving, communication, and teamwork skills.
Ability to work in a dynamic and fast-paced information technology data quality team environment servicing the healthcare industry.

Recommended Skills

Comfortable working with large data sets and databases.
Basic understanding of data management fundamentals: ETL, data governance, and data quality.
Familiarity with cloud platforms like AWS, GCP, or Azure.
Knowledge of software development methodologies and processes.
Understanding of data warehousing…


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