Senior Analytics Engineer

About the Role

Key Responsibilities

• Design and build scalable data pipelines using python, SQL, and cloud-based tools (Azure, AWS).
• Develop and maintain analytics models and data transformation processes using dbt, airflow, and data warehouses like Snowflake or BigQuery.
• Build and manage dashboards and data visualizations using web-based tools such as Tableau and Power BI.
• Ensure data quality, governance, and security compliance across engineering workflows.
• Responsible for ingestion, integration, and delivery of data products and insights across multiple platforms, maintaining data integrity and governance rules.
• Support adhoc analytics initiatives for clinical trials, commercial operations, and digital health systems.
• Utilize supervised or unsupervised learning methods to derive insights from large datasets, including unstructured text.
• Develop high-quality analytical and statistical models, insights, and visualizations to improve decision-making in manufacturing operations.
• Document all technical work within and outside formal document management systems.

Requirements

• Masters degree or PhD in Public Health, Economics, Statistics, Computer/Data Science, or related field.
• At least 5 years of experience in data engineering, analytics, or applied machine learning.
• Strong Python and SQL skills, with experience in ETL orchestration tools such as Airflow, Prefect, or Domino.
• Proficiency in modern data stack tools including dbt, Snowflake or BigQuery, version control, and CI/CD pipelines.
• Experience with DataOps/MLOps frameworks and AI/LLM tooling such as OpenAI, Langchain, Hugging Face Transformers.
• Strong communication and stakeholder engagement skills.
• Experience working in regulated industries such as pharma, biotech, or life sciences is highly preferred.
• Solid understanding of data science fundamentals including causal inference, regression, classification, and experimental design.
• Knowledge of deep learning methods for NLP, and experience working with unstructured text data.

Nice to Have

• Knowledge of GxP, HIPAA, or compliance standards.
• Experience with data modeling in clinical trials, real-world evidence (RWE), or commercial analytics.
• Familiarity with NLP, time series forecasting, or image analytics in healthcare.

Qualifications

• Masters degree or PhD in relevant fields.
• Minimum 5 years of relevant experience in data engineering, analytics, or machine learning.

Benefits & Perks

• Pay rate of $80-$95 per hour.