Data Engineer Lead

Profile - Data Engineer Lead

Exp- 7+ Years

Location - Noida

Work Mode - Hybrid

Skills - Data Engineering , Team Lead , Snowflake , AWS/Azure , Databricks , DBT , Data Warehousing

for applying you can share your CV on yogendra.jsohi@vservit.com

Key Responsibilities

Data Engineering & Pipeline Development:

·      Develop and maintain robust, scalable ETL pipelines to ingest, clean, and transform public (e.g., CMS, Medicaid), private (e.g., commercial claims, EHRs), and purchased (e.g., Clarivate, Doceree) datasets.

• Optimize data workflows and storage solutions to enhance data accessibility and usability for analytics and business intelligence teams.
• Implement data quality frameworks, ensuring the integrity and accuracy of healthcare datasets used for decision-making.
• Collaborate with data architects to design and enhance data models, ensuring efficient query performance and integration across multiple sources.

Collaboration with External Vendors & Partners:

• Work closely with external data vendors, research organizations, and commercial agencies to define projects, ensure data consistency, and improve ingestion processes.
• Provide technical oversight on vendor-sourced data projects, ensuring compliance with Avalere’s data quality and governance standards.
• Support the evaluation and acquisition of new datasets, integrating them into Avalere’s data ecosystem for analytics and modeling.

Internal Team Leadership & Support:

• Partner with data scientists, analysts, and market access teams to develop data solutions that drive business insights.
• Provide technical mentorship to junior data engineers, ensuring best practices in data pipeline development, automation, and cloud-based infrastructure.
• Work cross-functionally with data architects and analytics teams to align data engineering efforts with business and research objectives.

Required Skills and Experience

Education:

• Bachelor’s degree in computer science, information systems, data engineering, or a related field. Master’s degree preferred.

Technical Expertise:

• Extensive experience in building and managing ETL pipelines for large-scale healthcare data processing.
• Strong knowledge of public healthcare datasets, including Medicare/Medicaid claims, state health registries, and government-funded research data.
• Experience with private-sector datasets, such as commercial claims, EHRs, and provider-generated data.
• Proficiency in SQL, Python, and Spark for large-scale data processing and transformation.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and big data technologies (Databricks, Snowflake, Hadoop).
• Deep understanding of data modeling, data warehousing, and governance best practices.
• Experience implementing data security and compliance frameworks, including HIPAA, HITRUST, and other healthcare regulations.

Professional Experience:

• 8+ years of experience in data engineering, pipeline development, or a related field, preferably within healthcare, consulting, or analytics.
• Demonstrated ability to integrate, process, and optimize multi-source datasets for analytics and research applications.
• Experience managing data acquisition projects and working with external vendors to refine data ingestion approaches.

Proven track record in developing scalable cloud-based data solutions for enterprise-wide use.