Data Engineer

Summary In this role, you will be responsible for building out key components of data ingestion and transformation, using a combination of strong Java/Scala development skills as well as Big Data processing technologies. As a member of the team, you will be expected to take ownership of individual platform components and help set the vision and architecture for it. In the process, you will identify the requirements of new features, and propose design and drive the solution. Minimum Requirements Education & Experience: Bachelor’s degree in Computer Science, Engineering, or similar disciplines and 5 or more years of professional experience, or can convincingly demonstrate this level of skill. Knowledge and Skills Expertise writing clear, maintainable, production-level code in Python. Experience with cloud platforms such as Azure, AWS, or Google Cloud. Experience with containerized application development with Docker or Podman. Expertise on ETL pipelines, data migration, data cleaning. Experience with big data pipelines (Apache Spark, Kafka, AirFlow) is a plus. Experience with deep learning frameworks, such as Pytorch, is a plus. Experience with machine learning frameworks such as SKLearn, AutoML is a plus. Experience with vectors, matrix, dataframe libraries such as Numpy, Pandas is a plus. Expertise on best practices for data governance, curation, validation, integrity. Expertise on version control best practices. Experience with relational and non-relational databases. Experience preparing well-documented, reproducible results for external stakeholders. Preferred Experience Expertise in setting up cloud architecture, particularly in AWS. Experience working on a collaborative codebase with data science and engineering. Data science, analytics, or machine learning. Experience within a particular domain such as healthcare, logistics, genomics. Open source ecosystem contributions or expertise. Values & Abilities Aptitude to independently learn new technologies, prototype and propose software design and solutions. Ability to communicate effectively across academia and industry. Team-player who can collaborate effectively across many teams within the University. Open-minded and assertive when collaborating and working within our team and with other groups within Northeastern University. Entrepreneurial mind‑set with an ability to navigate complex structures and processes. Key Responsibilities & Accountabilities 40% - Build, maintain and improve data pipelines, infrastructure and tools to support Institute projects and operations in data science and AI. 10% - Support data scientists and other end users such as faculty and postdocs. 20% - Support delivery of practicum courses and other academic programs as subject matter expert. 30% - Participate in delivery of projects at the AI Solutions Factory to solve AI problems of industry partners. Position Type Information Technology. Additional Information Northeastern University considers factors such as candidate work experience, education and skills when extending an offer. Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness and life, retirement- as well as commuting and transportation. For more information, visit #J-18808-Ljbffr