Senior Data Engineer
On-siteStafford, Texas, United States
Job Summary
Design, construct, and manage scalable ETL/ELT pipelines to ingest, clean, and transform raw chemistry data for ML workflows. Develop optimized data models and data warehouses to support feature engineering on complex time-series and spectral datasets. Collaborate with Machine Learning Engineers to containerize models, build automated retraining pipelines, and implement robust data quality checks. Develop internal tools and APIs to facilitate data access and standardize interfaces for chemistry lab systems. Apply Python, cloud infrastructure, and orchestration tools to ensure the integrity and reproducibility of chemical experiment data used in analysis.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field (or equivalent practical experience)
- Expert-level proficiency in Python (including packages like Pandas, NumPy, and familiarity with data engineering libraries)
- Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP, preferred Azure), including services related to computing, storage, and serverless functions (e.g., Azure Data Lake Storage (ADLS), Azure Compute VMs, Azure Functions)
- Proven experience building and managing data workflows using an orchestration tool like Apache Airflow, Prefect, or Dagster
- Strong knowledge of SQL and experience working with both relational (e.g., PostgreSQL) and NoSQL databases
- Proficient with Git and standard DevOps practices
- Prior experience handling and processing complex, large-volume scientific data (e.g., mass spectrometry, chromatography, LIMS/ELN integration)
- Familiarity with MLOps platforms and tools such as Azure ML Studio, MLflow, Kubeflow, or Sagemaker
- Basic understanding of analytical chemistry concepts, such as chromatography fundamentals (e.g., retention time, peak integration) and relevant file formats
- Authorization to work in the United States without restriction or sponsorship
- Professional working proficiency in English is a requirement, including the ability to read, write and speak in English
- Strong analytical and problem-solving skills with a focus on delivering high-quality, reproducible data solutions
- Excellent verbal and written communication skills, with the ability to bridge the gap between technical infrastructure, data science models, and chemical applications
Desired Qualifications
- Azure
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