Data Engineer III

NBME•Philadelphia, PA

1d•Hybrid

About The Position

NBME is seeking a Data Engineer to join a growing team of data engineers and BI developers. The team has launched and continues to enhance an AWS data product for medical doctors. The role uses data engineering and problem-solving skills to deliver insights to internal staff and external customers, while modernizing, expanding, and optimizing NBME’s data platform. This includes building data lakes, complex data integration pipelines, and scalable data solutions for analytics, AI/ML, and business decision-making. The role also applies AI-assisted engineering practices to improve development efficiency and shares related best practices across the IT organization. The position is primarily hybrid, and NBME is prioritizing applicants within a 50-mile radius of its Philadelphia office. Onsite interviews and onboarding at the Philadelphia office may be required, with advance notice where applicable. The Data Engineer works with subject matter experts, analysts, architects, and engineering colleagues to develop data architectures and products, maintain data quality and security, and deliver work in an agile environment. NBME is a not-for-profit organization focused on assessments and learning tools for physicians and health professionals. Its mission is to advance assessment of these professionals to support optimal care and a highly effective, diverse, and compassionate healthcare workforce.

Requirements

Bachelor’s degree in Computer Science or a related technical field and six years of relevant work experience.
At least three years of Data Engineering and Data Warehousing experience.
At least two years of Python experience.
At least two years of experience with data integration tools such as Informatica, Boomi, or AWS Glue.
At least one year of experience with AWS services such as S3 and Redshift.
Expertise in data modeling, database management, and data profiling, particularly in Data Warehousing, Master Data Management (MDM), and Business Intelligence solution design and delivery.
Deep understanding of industry standards and best practices.
Strong analytical skills working with structured and unstructured datasets.
Critical thinking, creative problem-solving, and strong communication skills with stakeholders throughout the organization.
High proficiency in PL/SQL.
Experience with relational SQL and NoSQL databases, including Oracle, MS SQL Server, and HBase.
Experience with data integration tools such as Informatica, Boomi, Fivetran, MS Integration Services, and Sqoop.
Experience with at least one cloud vendor and its services, such as AWS, Google, Microsoft, or Snowflake.
Experience consuming and building APIs.
Experience with object-oriented or object-function programming languages such as Python, Java, C++, or Scala.
Experience with visual analytics tools such as QlikView, Tableau, Power BI, or MicroStrategy.
Experience using Agile methodology for development.

Nice To Haves

Master’s degree.
Experience with Singer and DBT.

Responsibilities

Participate in requirements gathering and analyze and architect project and system data architectures.
Collaborate with subject matter experts, data analysts, solutions architects, and enterprise architects to ensure designs align with enterprise architecture standards and the existing environment.
Contribute as a critical member of an agile scrum team and help ensure sprint deliverables are met.
Train and mentor team members.
Manage time independently across multiple priorities and projects.
Protect the integrity, accuracy, and security of corporate data.
Ensure high data quality for Data Services, Analytics, and Master Data Management.
Perform logical and physical data modeling with an agile mindset.
Build automated, scalable, test-driven data pipelines.
Use software development practices including Git version control, CI/CD, and release management.
Build data products using visualization, BI, and data science tools.
Collaborate with Data Engineers, DevOps engineers, and architects to identify improvements to DataOps tools and frameworks.
Provide agile capabilities and services in support of digital transformation.