Sr. Platform Engineering Lead

Bayer•Chesterfield, MO

1d•$192,275 - $195,000•Hybrid

About The Position

Bayer Research & Development Services LLC is hiring multiple Sr. Platform Engineering Leads for Chesterfield, Missouri. The role leads design sessions for data processing, storage, and delivery solutions; evaluates emerging technologies through proofs of concept and presents findings; implements data solutions according to design documentation; and improves delivery quality through code reviews, retrospectives, and functional and integration testing. The position also mentors and trains junior data engineers and provides technical leadership to data engineering teams. The role builds and leads scalable, secure data solutions across multi-cloud platforms. Responsibilities and qualifications involve ETL pipelines for terabyte-size datasets, data marts and distributed data processing, least-privilege data access, real-time pipeline monitoring and alerting, and cost and resource optimization using FinOps principles. The role is based in Chesterfield, MO. Telecommuting from a home office within reasonable commuting distance is permitted up to two days per week. Up to 5% domestic and international travel is required. The stated salary range is $192,275 to $195,000; additional compensation may include a bonus or commission, if relevant. Benefits include health care, vision, dental, retirement, PTO, and sick leave. Salary may vary based on location, market data, skills, relevant experience, degrees, certifications, and other factors.

Requirements

A master's degree in Computer Science, Information Systems, Computer Engineering, or a closely related field and at least 2 years of experience in the stated areas; alternatively, a bachelor's degree in those fields and 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 (IaaC) 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, UDFs, and stored procedures to build scalable data marts, enable distributed data processing, and enforce secure, least-privilege data 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 drive cost efficiency and resource optimization strategies.
Experience leading and training data engineering teams, including providing technical guidance during code reviews and evaluations of emerging technologies for platform enhancement.
Ability to travel up to 5% within the U.S. and internationally.

Responsibilities

Lead design sessions for data processing, storage, and delivery solutions.
Initiate and lead evaluations of new technologies, including proofs of concept, and present results.
Implement data solutions in accordance with 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 evaluation of emerging technologies for platform enhancement.
Develop 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.
Implement real-time data pipeline alerting systems using cloud monitoring platforms.
Apply FinOps principles to drive cost efficiency and resource optimization.