Title: Senior Data Engineer (DBT & Databricks)
Job Type: Full-Time/Permanent
Location: Pune, India (REMOTE)
About the Role
- Plumlogix is seeking a skilled Data Engineer with strong DBT and Databricks experience to support a strategic enterprise data modernization initiative. This role will play a critical part in building and expanding a modern analytics platform designed around a Medallion Architecture, semantic data models, and trusted data products that empower business users and agency partners with reliable insights.
- The ideal candidate will have hands-on experience developing data models, building scalable data pipelines, implementing data quality frameworks, and supporting healthcare analytics solutions within Databricks and DBT Cloud environments.
Project Overview
The client is building a next-generation analytics platform leveraging Databricks and DBT Cloud. The current MVP phase is expected to conclude by the end of July, after which the selected consultant will help scale the platform over the next 12+ months by migrating and modernizing legacy analytics workloads into the new DBT-led architecture.
The goal is to establish a trusted data ecosystem that enables users to:
- Discover and understand enterprise data assets
- Trust data through governance and quality controls
- Consume curated semantic models for analytics and reporting
- Support critical reporting needs for healthcare agency partners
Key Responsibilities
- Develop and maintain DBT models, transformations, semantic layers, and analytics-ready datasets
- Build and support Databricks pipelines using modern data engineering best practices
- Design and implement Medallion Architecture (Bronze, Silver, Gold layers)
- Develop scalable ELT workflows leveraging Databricks Auto Loader and Delta Lake capabilities
- Support migration efforts from Azure Data Factory (ADF) to Databricks-native solutions
- Implement data governance, lineage, documentation, and metadata management processes
- Create and maintain data quality testing frameworks within DBT
- Collaborate with architects, analysts, and business stakeholders to deliver trusted data products
- Optimize SQL and Python-based transformations for performance and scalability
- Participate in deployment, monitoring, support, and operational activities
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or a related field from a recognized institution.
- 4 years of hands-on experience with DBT Cloud
- 4 years of hands-on experience with Databricks development and support
- Strong experience building and maintaining semantic data models
- Strong experience with SQL, Python, and PySpark.
- Experience building ELT/ETL pipelines in cloud data environments
- Hands-on experience with Databricks Auto Loader and Delta Lake
- Experience working with Medallion Architecture and modern lakehouse patterns
- Strong understanding of data modeling concepts and analytics engineering practices
Ideal Candidate Profile
The ideal candidate is a hands-on Data Engineer/Analytics Engineer who enjoys building modern data platforms from the ground up. They possess strong DBT modeling expertise, understand healthcare data challenges, and can collaborate effectively with architects and business stakeholders to create trusted, scalable, and governed analytics solutions.
Estimated Allocation
- 50% DBT Modeling, Semantic Layer Development & Analytics Engineering
- 25% Databricks Pipeline Development & Platform Support
- 25% Data Governance, Data Quality, Testing & Documentation
Preferred Qualifications
- DBT Certification
- Databricks Developer Certification
- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or a related field from a recognized institution
- Experience developing healthcare analytics and reporting solutions
- Familiarity with healthcare data models, regulatory considerations, and reporting requirements
- Experience delivering trusted datasets for healthcare business users and stakeholders
