Software Engineer 2 ( Data )

You will design, develop, and maintain scalable data pipelines, transformations, and data models that convert complex data into trusted datasets for analytics, reporting, and operational insights.

You will implement data quality, monitoring, and reliability practices to ensure data accuracy, availability, performance, and operational excellence across data platforms and pipelines.

You will partner with business stakeholders, program managers, and engineering teams to translate business requirements into scalable technical solutions and actionable data products.

You will contribute to the design, automation, and continuous improvement of data platform capabilities, including deployment processes, CI/CD pipelines, metadata management, and operational tooling.

You will support live-site operations by investigating data issues, responding to incidents, implementing corrective actions, and improving platform resiliency to reduce recurring problems.

You will collaborate across teams to share best practices, improve engineering standards, evaluate emerging technologies, and drive adoption of modern data engineering capabilities.

Bachelor's Degree in Computer Science, Information Technology, or related field AND 8+ years technical experience in software engineering, network engineering, service engineering, or systems engineering OR equivalent experience. 5+ years of hands on Experience in managing data and data related technologies.

designing, developing, or supporting data pipelines, ETL/ELT processes, data models, or analytical solutions.

with SQL and one or more modern data engineering technologies such as Spark, Python, PySpark, Scala, data warehouses, or cloud-based data platforms.

working with business stakeholders to translate business requirements into technical solutions.

developing scalable data solutions using SQL, Python, PySpark, Spark SQL, or other distributed data processing technologies, including data modeling and ETL/ELT pipeline development.

implementing data engineering operational practices, including source control, CI/CD, automated testing, monitoring, data quality management, and DevOps methodologies.

delivering enterprise analytics and reporting solutions, partnering with business stakeholders to transform complex operational data into actionable insights while applying appropriate governance, privacy, and compliance practices.