Description

You will work as an individual contributor on a data engineering team to develop and deploy automated data products.

Responsibilities

• Design, develop, and review real-time and bulk data pipelines from sources including APIs, streaming data, data warehouses, messages, images, and video.
• Apply DataOps best practices including version control, PR-based development, CI/CD, deployment automation, and test automation.
• Develop documentation for data lineage and data dictionaries to support the enterprise data model.
• Collaborate within cross-functional, distributed agile teams to innovate analytic solutions.
• Write production-quality Python and SQL code following established design patterns for data ingest, transformation, and egress.

Required Skills

• Proven experience in production-level Python development and designing high-quality codebases.
• Strong expertise in SQL development and designing production SQL codebases.
• Experience with data modeling and software engineering best practices.
• Knowledge of ML systems architecture and data science workflows, including data wrangling, model training, and deployment at scale.
• Proficiency in applying CI/CD, schema change control, and monitoring within data engineering projects.
• Experience working in Agile environments using Scrum or Kanban.
• Bachelor’s degree in engineering, computer science, or an analytical field (Statistics, Mathematics) with 3 years of experience, or a Master’s/Ph.D. with 1 year of experience.
• Familiarity with Azure DevOps and Azure environments.

Preferred Skills

• Working knowledge of Azure Stream Architectures, DBT, and Azure Machine Learning Environment.
• Experience with GIS data, schema change tools, and data dictionary tools.
• Understanding of Object-Oriented Programming principles and distributed systems.

Key Skills

Education

ANY GRADUATE