Data Engineer

Bayer•Creve Coeur, MO

About The Position

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice. Data Engineer We are seeking a highly motivated data engineer with demonstrated experience scaling and delivering production quality data systems to join our Science team within Digital Farming Solutions at Bayer Crop Science. You will work closely with key partners, including data engineers and data scientists, to develop reliable, scalable and maintainable machine learning solutions.

Requirements

Bachelor’s degree in data science, computer science, or related quantitative field
A minimum of 3 years' experience is required for the following
Strong Python coding skills for development and visualizations, including experience with standard packages (numpy, pandas, matplotlib, seaborn)
Familiar with Extract, Transform, and Load (ETL) processes and simple pipeline creation
Proficient use of SQL or Spark to extract and manipulate data from databases, data warehouses, and data lakes
Experience utilizing Git for collaborative code development
Experience with cloud-based platforms (AWS, GCP, Azure) and basic services (ie. S3, Lambda, Dataproc)
Experience with oral presentation and technical writing
Practical experience with newline-delimited data formats
Familiarity with text encoding (UTF-8) and common cleaning issues
Familiarity with tokenization concepts and context-window tradeoffs
Experience with prompt templates and basic prompt telemetry for debugging

Nice To Haves

Excitement to learn new topics, develop new skills and use new tools
Experience with web services, api and database design
Experience applying data quality concepts
Familiarity with NOSQL tools like Hadoop (hive, pig, presto) and PySpark
Experience with virtual machines and cloud computing
Interdisciplinary communication and collaboration skills
Experience with application of statistics to environmental or agricultural problems
Expertise in data interoperability and analytics
Familiarity with NLP libraries and tokenizers
Familiarity with embeddings, vector DBs, and data-labeling workflows

Responsibilities

Write robust, well-documented code
Engage with colleagues with diverse technical backgrounds and expertise to understand feature, model and business requirements, and develop solutions to meet automation and scaling needs
Evaluate existing data and model pipelines, and provide recommendations to support business and technical requirements
Utilize tools and/or infrastructure developed by technical delivery partners to ensure proper data architectures and computational infrastructure is available to support rapid development and testing on machine and deep learning models that create value for our farmers
Collaborate across the Science organization to create high-quality, reproducible tools (e.g. templates, packages and dashboards) that will accelerate delivery of customer value
Undertake written & verbal communication with stakeholders in various parts of the organization in the form of detailed documentation and presentations
Chunk, clean, and format text into LLM-ready formats such as JSONL
Contribute to community guidelines for prompt/data hygiene, provenance, and safe data handling for LLMs