Sr. Platform Engineering Lead

Bayer•Chesterfield, MO

1d•$192,275 - $195,000•Hybrid

About The Position

Bayer Research and Development Services LLC is hiring multiple Sr. Platform Engineering Leads in Chesterfield, Missouri. The role leads design sessions for data processing, storage, and delivery solutions; evaluates emerging technologies through proof-of-concepts and presents results; implements data solutions from design documentation; and improves delivery quality through code reviews, retrospectives, and functional and integration testing. The role also mentors and trains junior data engineers and leads data engineering teams. The position focuses on building and operating scalable, secure data platforms and pipelines across multi-cloud environments. Responsibilities include developing ETL pipelines for terabyte-size datasets; creating data marts and distributed data processing solutions; implementing monitoring and real-time alerting; and applying FinOps principles to improve cost efficiency and resource utilization. The position is based in Chesterfield, Missouri. Telecommuting from a home office within reasonable commuting distance of Chesterfield is permitted up to two days per week. Up to 5% domestic and international travel is required.

Requirements

Master’s degree in Computer Science, Information Systems, Computer Engineering, or a closely related field, plus at least 2 years of experience in the stated areas; alternatively, a bachelor’s degree in one of those fields plus 5 years of progressive, post-bachelor’s experience in the stated areas.
Experience using Java, Python, JavaScript, and/or Scala to build scalable ETL pipelines for terabyte-size datasets.
Experience optimizing ETL pipeline performance, reliability, and security using APIs and encryption tools.
Experience applying infrastructure as code (IaC) and version control to data pipelines.
Experience using Kafka, Spark, Airflow, IAM, AWS, and GCP to develop scalable and secure data pipelines on multi-cloud platforms.
Experience using Redshift, BigQuery, SQL, user-defined functions (UDFs), and stored procedures to build scalable data marts, enable distributed data processing, and enforce secure, least-privilege access with row- and column-level security.
Experience using cloud monitoring platforms, including AWS CloudWatch and Google Cloud logging, to implement real-time data pipeline alerting systems.
Experience applying FinOps principles to cost efficiency and resource optimization.
Experience leading and training data engineering teams, including technical guidance during code reviews and evaluations of emerging technologies.
Able to travel up to 5% in the United States and internationally.

Responsibilities

Lead design sessions for data processing, storage, and delivery solutions.
Initiate and lead evaluations of new technologies, including proof-of-concepts, and present results.
Implement data solutions according to design documentation.
Lead code reviews, retrospectives, and functional and integration testing to improve delivery quality.
Mentor and train junior data engineers.
Lead and train data engineering teams, providing technical guidance during code reviews and evaluations of emerging technologies for platform enhancement.
Build scalable ETL pipelines for terabyte-size datasets and optimize their performance, reliability, and security.
Develop scalable and secure data pipelines on multi-cloud platforms.
Build scalable data marts, enable distributed data processing, and enforce secure, least-privilege data access with row- and column-level security.
Use cloud monitoring platforms to implement real-time data pipeline alerting systems.
Apply FinOps principles to drive cost efficiency and resource optimization strategies.