Director, Analytics Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and develop intelligent, self-healing data pipelines utilizing AI/ML for automated data quality monitoring, anomaly detection, and remediation.

• Create and manage centralized feature stores for reuse across various models and applications.

• Establish curated data repositories that are optimized for data science and AI workflows, which include training datasets, evaluation datasets, and production serving layers.

• Develop automated feature engineering pipelines with tracking of data lineage.

• Collaborate with Enterprise IT to enhance the architecture of analytics platforms for high-performance data science workloads.

• Construct automated pipelines that integrate sales, CRM, patient claims, real-world evidence, and unstructured data.

• Develop self-service data access layers to facilitate independent data querying and extraction.

• Set SLAs for data availability, freshness, and quality.

• Implement monitoring and observability solutions.

• Lead teams in the construction of enterprise-scale data platforms and feature stores.

⛳️ Requirements

• An advanced degree in Computer Science, Data Engineering, or a related field.

• Over 7 years of experience in data engineering, ML/AI engineering, or analytics infrastructure.

• More than 5 years of experience leading teams in the development of enterprise-scale data platforms and feature stores.

• Expert knowledge of feature store technologies such as Feast, Tecton, SageMaker Feature Store, and Databricks Feature Store.

• Profound expertise in modern data platforms optimized for ML workloads, including Databricks, Auto ML, Snowflake, and BigQuery.

• Strong skills in Python, SQL, and Spark/PySpark for large-scale data processing.

• Experience with data orchestration tools like Airflow, Prefect, and dbt, as well as CI/CD for data pipelines.

• Understanding of data governance, privacy (HIPAA, GDPR), and compliance within the life sciences sector.

• A proven history of implementing AI/ML-powered automation in data engineering workflows.

• Experience in the pharmaceutical, healthcare, or life sciences industries.

• Familiarity with streaming technologies, MLOps tools, and data lakehouse architectures.

• Must reside in the U.S.; the position can be performed remotely from anywhere within the U.S., subject to potential legal-entity restrictions.

• Willingness to travel up to 20%.

🏝️ Benefits

• Performance-based cash incentive.

• Eligibility for consideration for annual equity awards, depending on the role level.

• Comprehensive health benefits.

• Life insurance benefits.

• Disability coverage.

• 401(k) plan with company contributions and matching.

• Vacation time.

• Personal days.

• Paid holidays.

• Additional leave options.

• Reasonable accommodations for individuals with disabilities.