SPECTRAFORCE
Overview
Job Overview: Client is seeking a highly experienced Senior Analytics Engineer to serve as a key contributor in building advanced analytics infrastructure and AI-driven decision support tools for the Global Patient Operations Cell Therapy team. This role blends data engineering, analytics engineering, and AI/ML integration to enhance visibility into critical operations such as scheduling, clinical trials, and commercial performance. The ideal candidate thrives in regulated environments, understands the nuances of healthcare data, and can own delivery end-to-end from data ingestion through to dashboarding and insight delivery. Base pay range
$80.00/hr - $85.00/hr Location
Seattle, WA Eastlake (50% onsite) Duration
12 months Employment type
Contract Tools/Skills
Analytics Eng dbt, SQL Modelling, datamarts, Tableau/Power BI, metrics definition, insights and data storytelling, Adobe Analytics Advanced analytics Scikit-learn, TensorFlow, PyTorch, MLflow, feature engineering AI Tools OpenAI API, LangChain, Retrieval-Augmented Generation (RAG) MLOps/Deployment Required Qualifications
5+ years of experience in data engineering, analytics or applied machine learning Strong Python and SQL skills; experience in ETL orchestration tools (Airflow, Prefect, Domino); ability to manipulate and analyze complex datasets Proficiency in modern data stack (dbt, Snowflake/BigQuery, version control, CI/CD pipelines) Experience with DataOps/MLOps frameworks and AI/LLM tooling (OpenAI, Langchain, Hugging Face Transformers) Strong communication and stakeholder engagement skills Experience in regulated industry (Pharma, biotech or life sciences) is highly preferred Solid grasp of data science fundamentals: causal inference, regression, classification, experimental design Nice to Have
Knowledge of GxP, HIPAA or compliance standards Experience with data modelling in clinical trials, real world evidence (RWE) or commercial analytics Familiarity with NLP, time series forecasting, or image analytics in healthcare Masters degree or PhD in Public Health, Economics, Statistics, Computer/Data Science, or related field Responsibilities
Design and build scalable data pipelines using Python, SQL and cloud-based tools (Azure, AWS) Develop and maintain analytics models and data transformations using dbt, Airflow and data warehouses (e.g., Snowflake, BigQuery) Build and manage dashboards and data visualizations using web-based tools (Tableau, Power BI) Ensure data quality, governance and security compliance across engineering workflows Ingest, integrate and deliver data products and insights across multiple platforms with data integrity and governance Apply and maintain knowledge of deep learning methods for NLP (quantitative area of study, Computer Science preferred) Support ad hoc analytics initiatives for clinical trials, commercial ops and digital health systems Utilize supervised or unsupervised methods to derive insights from large unlabeled datasets Work with unstructured text data Develop high-quality analytical and statistical models, insights and visualizations to improve decision making in manufacturing operations Document all technical work within and outside of formal document management systems Seniority level
Mid-Senior level Other
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Job Overview: Client is seeking a highly experienced Senior Analytics Engineer to serve as a key contributor in building advanced analytics infrastructure and AI-driven decision support tools for the Global Patient Operations Cell Therapy team. This role blends data engineering, analytics engineering, and AI/ML integration to enhance visibility into critical operations such as scheduling, clinical trials, and commercial performance. The ideal candidate thrives in regulated environments, understands the nuances of healthcare data, and can own delivery end-to-end from data ingestion through to dashboarding and insight delivery. Base pay range
$80.00/hr - $85.00/hr Location
Seattle, WA Eastlake (50% onsite) Duration
12 months Employment type
Contract Tools/Skills
Analytics Eng dbt, SQL Modelling, datamarts, Tableau/Power BI, metrics definition, insights and data storytelling, Adobe Analytics Advanced analytics Scikit-learn, TensorFlow, PyTorch, MLflow, feature engineering AI Tools OpenAI API, LangChain, Retrieval-Augmented Generation (RAG) MLOps/Deployment Required Qualifications
5+ years of experience in data engineering, analytics or applied machine learning Strong Python and SQL skills; experience in ETL orchestration tools (Airflow, Prefect, Domino); ability to manipulate and analyze complex datasets Proficiency in modern data stack (dbt, Snowflake/BigQuery, version control, CI/CD pipelines) Experience with DataOps/MLOps frameworks and AI/LLM tooling (OpenAI, Langchain, Hugging Face Transformers) Strong communication and stakeholder engagement skills Experience in regulated industry (Pharma, biotech or life sciences) is highly preferred Solid grasp of data science fundamentals: causal inference, regression, classification, experimental design Nice to Have
Knowledge of GxP, HIPAA or compliance standards Experience with data modelling in clinical trials, real world evidence (RWE) or commercial analytics Familiarity with NLP, time series forecasting, or image analytics in healthcare Masters degree or PhD in Public Health, Economics, Statistics, Computer/Data Science, or related field Responsibilities
Design and build scalable data pipelines using Python, SQL and cloud-based tools (Azure, AWS) Develop and maintain analytics models and data transformations using dbt, Airflow and data warehouses (e.g., Snowflake, BigQuery) Build and manage dashboards and data visualizations using web-based tools (Tableau, Power BI) Ensure data quality, governance and security compliance across engineering workflows Ingest, integrate and deliver data products and insights across multiple platforms with data integrity and governance Apply and maintain knowledge of deep learning methods for NLP (quantitative area of study, Computer Science preferred) Support ad hoc analytics initiatives for clinical trials, commercial ops and digital health systems Utilize supervised or unsupervised methods to derive insights from large unlabeled datasets Work with unstructured text data Develop high-quality analytical and statistical models, insights and visualizations to improve decision making in manufacturing operations Document all technical work within and outside of formal document management systems Seniority level
Mid-Senior level Other
Referrals increase your chances of interviewing at SPECTRAFORCE. Get notified about new Data Engineer jobs in Seattle, WA. #J-18808-Ljbffr