What are the responsibilities and job description for the Senior Tech Lead - Clinical Data Engineering/ Data Platforms position at V.L.S. Systems, Inc?
We are seeking a Senior Technical Leader to provide hands-on technical leadership for clinical data engineering, data platform development, and analytics delivery. This role will lead the design and execution of scalable data pipelines, Lakehouse architecture, cloud services integration, and delivery governance across active clinical data initiatives.
About the Role
The ideal candidate will have strong experience with Databricks Lakehouse, Delta Lake, Unity Catalog, Medallion architecture, SQL Warehouses, AWS services, data engineering delivery, agile execution, and stakeholder management in a life sciences or regulated data environment
Responsibilities
- Serve as the technical lead for clinical data engineering and platform delivery
- Own architecture and implementation across Databricks Lakehouse, Delta Lake, Unity Catalog, Medallion architecture, and SQL Warehouses
- Lead end-to-end delivery of data pipelines, curated datasets, data products, and analytics-ready data assets
- Manage and guide a team of 5 10 data engineers across onsite and offshore delivery
- Provide technical direction on pipeline design, data modeling, performance optimization, security, scalability, and production readiness
- Work with AWS services such as S3, EMR/Athena, Secrets Manager, IAM, and related cloud platform components
- Drive sprint planning, backlog management, technical design reviews, code reviews, release planning, and delivery governance
- Partner with Clinical Operations, Biostatistics, Data Management, IT, data managers, and business stakeholders to translate requirements into technical solutions
- Coordinate cross-functional delivery across data engineering, analytics, AI/ML, platform, QA, and business tea
- Ensure engineering outputs meet quality, security, compliance, performance, and maintainability expectations
- Support issue resolution across data ingestion, transformation, pipeline failures, data quality defects, and platform dependencies
- Provide technical oversight for automation, AI/ML-enabled workflows, and human-in-the-loop data operations where applicable
Required Qualifications
12 years of experience in data engineering, data architecture, analytics engineering, or cloud data platform delivery.
Strong hands-on experience with Databricks Lakehouse, including:
o Delta Lake
o Unity Catalog
o Medallion architecture
o SQL Warehouses
o Notebook/job orchestration
o Data pipeline performance tuning
Working knowledge of AWS services including S3, EMR/Athena, Secrets Manager, IAM, and cloud-native security patterns.
Proven experience leading 5 10 data engineers and owning end-to-end technical delivery.
Strong understanding of data pipeline design, batch processing, data transformation, data modeling, and analytics enablement.
Experience with agile delivery, sprint ceremonies, backlog management, release management, and technical execution governance.
Ability to work in cross-functional delivery models involving technical teams, business users, data managers, and client stakeholders.
Strong stakeholder management and client-facing communication skills.
Ability to translate business and clinical data requirements into scalable technical architecture and implementation plans.
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Preferred Qualifications
Experience in pharma, biotech, CRO, clinical operations, or life sciences data environments.
Familiarity with clinical data domains, study data, lab data, safety data, EDC data, or biostatistics workflows.
Experience working with AI/ML, automation, or metadata-driven data pipelines.
Knowledge of data governance, data quality, lineage, auditability, and regulated data controls.
Experience with CI/CD, Git-based development, DevOps practices, and production support models.
Experience managing distributed onsite/offshore delivery teams.
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Key Skills
Databricks, Delta Lake, Unity Catalog, Medallion Architecture, SQL Warehouses, AWS S3, EMR, Athena, Secrets Manager, IAM, Data Engineering, Data Architecture, Pipeline Development, Data Modeling, Agile Delivery, Sprint Management, Technical Leadership, Clinical Data Platforms, Stakeholder Management, Offshore Team Leadership, Production Support.