Data Engineer Lead
2 weeks ago
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
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.
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