NovintiX
Fast-growing engineering and digital transformation consultancy serving Life Sciences, MedTech, and Healthcare clients across US, Ireland, and Europe. Specializing in digital programs, engineering services, and talent solutions that drive innovation, efficiency, and compliance.
Responsibilities:
- Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data integration and analytics solutions.
- Develop data engineering solutions using Python, PySpark, SQL, and Azure cloud technologies.
- Build and optimize batch and real-time data processing pipelines using Azure Databricks.
- Develop and orchestrate data workflows using Azure Data Factory (ADF).Perform data extraction, transformation, and loading activities from multiple structured and unstructured data sources.
- Design and maintain data models, data lakes, and cloud-based data platforms for analytics and reporting requirements.
- Optimize data processing performance through efficient Spark transformations, partitioning, and query tuning techniques.
- Collaborate with business analysts, data architects, and engineering teams to understand business requirements and deliver scalable data solutions.
- Ensure data quality, integrity, governance, and security standards across enterprise data platforms.
- Monitor and troubleshoot ETL jobs, pipeline failures, and performance bottlenecks.
- Implement CI/CD and deployment strategies for data engineering workflows and cloudbased solutions.
- Participate in Agile/Scrum ceremonies including sprint planning, daily stand-ups, and retrospectives.
- Create and maintain technical documentation, data flow diagrams, and operational support documents.
Required Skills:
- Bachelor's degree in computer science, Information Technology, or related field.
- 1-2 years of professional experience in Data Engineering and ETL development.
- Strong hands-on experience in Python, PySpark, and SQL development.
- Expertise in designing and developing ETL/ELT pipelines using Azure Data Factory and Azure Databricks.
- Strong understanding of data warehousing concepts, dimensional modeling, and big data processing.
- Experience working with Azure cloud services including Azure Data Lake, Azure SQL, and Azure Storage Accounts.
- Hands-on experience with Spark optimization techniques, data transformations, and distributed data processing.
- Experience handling large-scale, structured and unstructured datasets.
- Familiarity with REST APIs, JSON, Parquet, Delta Lake, and other modern data formats.
- Understanding CI/CD pipelines, Git version control, and DevOps practices.
- Knowledge of performance tuning, troubleshooting, and monitoring of ETL/data pipelines.
- Strong analytical, troubleshooting, and problem-solving skills.
- Effective stakeholder communication and requirements gathering skills.
- Experience working in regulated industries such as MedTech, Pharma, Healthcare, or Manufacturing is preferred.
- Hands-on experience with Python, PySpark, SQL, Azure Databricks, Azure Data Factory, Azure Data Lake, Git, and cloud-based data platforms.
Apply Now at [email protected]
Job Type: Full-time
Pay: ₹477,614.19 - ₹1,830,732.69 per year
Work Location: In person
