Director, Analytics Engineering (2 Openings)

About This Opportunity

Our talent team is representing a confidential life sciences organization seeking a Director, Analytics Engineering to lead the development of next-generation, AI-powered data infrastructure. This remote position (based anywhere in the U.S.) focuses on building automated data pipelines, scalable repositories, and enterprise feature stores that enable data science and analytics at scale. We have 2 openings available.

This role requires approximately 20% travel (domestic and international). The hiring manager will define specific working hours and travel expectations.

Responsibilities

• Design and implement intelligent, self-healing data pipelines leveraging AI/ML for automated data quality monitoring, anomaly detection, and remediation
• Build and maintain centralized feature stores enabling feature reusability across multiple models and use cases
• Create curated data repositories optimized for data science/AI workflows, including training datasets, evaluation datasets, and production serving layers
• Develop automated feature engineering pipelines that transform raw data into analytics-ready features with comprehensive lineage tracking
• Partner with Enterprise IT teams to optimize analytics platform architecture for high-performance data science workloads
• Build automated pipelines integrating diverse data sources including sales, CRM, patient claims, real-world evidence, and unstructured data
• Create self-service data access layers empowering data scientists and analysts to query and extract data independently
• Establish and monitor SLAs for data availability, freshness, and quality; implement observability solutions

What We're Looking For

Required:

• Advanced degree in Computer Science, Data Engineering, or related field
• 7+ years of experience in data engineering, ML/AI engineering, or analytics infrastructure
• 5+ years leading teams building enterprise-scale data platforms and feature stores
• Expert knowledge of feature store technologies (Feast, Tecton, SageMaker Feature Store, Databricks Feature Store)
• Deep expertise in modern data platforms optimized for ML workloads (Databricks, AutoML, Snowflake, BigQuery)
• Strong proficiency in Python, SQL, and Spark/PySpark for large-scale data processing
• Experience with data orchestration tools (Airflow, Prefect, dbt) and CI/CD for data pipelines
• Understanding of data governance, privacy regulations (HIPAA, GDPR), and compliance in life sciences

Preferred:

• Proven track record implementing AI/ML-powered automation in data engineering workflows
• Strategic thinking with ability to balance innovation with production stability
• Builder mindset creating scalable, self-service capabilities that reduce data engineering dependencies
• Experience in pharmaceutical, healthcare, or life sciences industry
• Knowledge of streaming technologies, MLOps tools, and data lakehouse architecture

How We Work With You

As Get A Job.ai recruiters, we connect exceptional talent with confidential opportunities. Here's our process:

1. Apply through the Get A Job.ai platform
2. Our recruiting team will screen your application and conduct an initial conversation
3. We'll submit qualified candidates to our client for consideration
4. Please do not contact the client organization directly

Pay

This position is remote within the United States. Relocation assistance is not available. Employment type is full-time, permanent.

Get A Job.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.