Senior Data Platform Engineer

Role Overview

• Help in designing, building, and operating the university’s shared data infrastructure – including data pipelines, medallion-layer and other framework data products, cloud and/or on-prem tooling, and the integration fabric that connects data systems across the university.
• Help realize the design and build of ETL/ELT and other data integration movement processes for the Reporting and Analytics Environment.
• Engage with other data engineers and enterprise/integration architects within the team.
• Collaborate with OTDI Infrastructure colleagues and specialists in designing and implementing integrations from multiple systems into the team's data environments.
• Work to obtain and refine data requirements, build data integration flows, partner with data and visualization analysts on query optimization and tuning, and confer with data governance resources on metadata requirements.
• Provide production support duties for the systems we manage; respond to help desk issues related to our systems, monitor the production support queue, and respond to data flow failures in a timely manner.
• Participate in rotating off-hours and weekend on-call/pager duty.

Requirements

• Bachelor's Degree with a Major in Computer & Information Science or equivalent experience;
• 4 years of experience in data & integration methodologies, technologies, and tools;
• Demonstrated deep understanding of SQL and hands-on experience implementing ETL/ELT best practices at scale;
• Experience with Python, Java, Scala, or other programming languages for data processing (Python preferred);
• Experience working with business and process analysts in gathering requirements as well as in collaborative data movement design and data governance;
• Proficiency in SQL across at least one analytical database platform (Redshift, Databricks, Snowflake, or equivalent);
• Demonstrated production experience with Apache Airflow (DAG authoring, operator development, environment administration);
• Experience with infrastructure-as-code in a team environment (modules, state management, CI/CD integration);
• Familiar with modern data analytics technologies and techniques, such as cloud-based analytics environments (AWS, Azure, GCP) serverless coding streaming and micro-batch data loads code automation continuous development delivery and integration;
• Familiarity with data catalog or metadata management tooling and practical understanding of data governance concepts;
• Experience with web services/APIs (REST, SOAP), S/FTP, and data interchange formats (JSON, XML, CSV);
• Strong interpersonal skills, including excellent customer service and relationship management skills;
• Detail-oriented and desire to continually keep up with advancements in data engineering practices;
• Strong written and verbal communication skills, including presenting complex topics to business teams and leadership;
• Ability to flex and adapt to changing environments and direction in team development goals;
• Must have experience working with both technical and business/process analysts in a fast-moving and high caliber environment.

Tech Stack

• Airflow
• Amazon Redshift
• Apache
• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• Java
• Python
• Scala
• SOAP
• SQL

Benefits

• Medical, dental and vision coverage, with Ohio State paying a significant portion of the cost.
• Paid time off, including sick and vacation time and 11 holidays.
• State retirement plan or an alternative retirement plan, both with generous employer contributions.