Senior Delivery Consultant - Data, Professional Services, AWSI, Healthcare and Life Sciences

Key job responsibilities
Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise HCLS environments, integrating with legacy systems and existing data governance frameworks.

Build data products that serve multiple downstream applications and use cases — from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale.

Operate with a high degree of autonomy within fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight.

Navigate complex data access, security, and privacy requirements unique to pharma and healthcare including GxP compliance constraints, HIPAA, and regulatory data governance frameworks.

Architect contextual knowledge layers, including ontologies and knowledge graphs leveraging AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with the vocabulary and guardrails to reason accurately and execute autonomously within regulated environments.

Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with teams across customer IT, business, and partner organizations.

Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures.

Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI-native for accelerated scale and pace.

Basic Qualifications

- Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or other related field
- Experience in advanced SQL & ability to write complex queries from scratch from multiple tables
- Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Preferred Qualifications

- Experience with compliance & security standards including PCI DSS, ISO 27001, HIPAA, and NIST
- 6+ years of solving problems with technology in the Healthcare/Life Sciences Industry experience
- Experience in any Bigdata architecture, or experience in Hive/Spark/Hbase/Yarn and experience in Kafka
- 4+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Experience in clinical data standards (OMOP, CDISC, FHIR)
- Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing data access patterns that support identity and least-privilege access
- Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges and conveying technical concepts to both technical and business audiences.
- Proficiency in AI-DLC or equivalent AI-accelerated development methodologies — including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments