Experience
6 - 11 yrs
Job Location
Chennai, India
Vacancy
1
Designation
Azure Data Engineer
Job Type
ONSITE
Job Description
Azure Data Tech Lead / Sr.Azure Data Engineer
Years of Exp- 6 to 8 Years
Location-Chennai
Work Mode- Work From Office -Chennai
Shift time-UK Shift time
Billrate- Ieyond this range)
Primary Skillset-Azure datafactory,Azure ,Python, Pyspark, Databricks, SQL,Azure Synapse
JD:
Experience with Azure datafactory,Azure ,Python, Pyspark, Databricks, SQL
Key Responsibilities
Design and build ETL/ELT pipelines to ingest, transform, and load data from clinical, omics, research, and operational sources.
Optimize performance and scalability of data flows using tools like Apache Spark, Databricks, or AWS Glue.
Collaborate with domain experts in genomics, clinical trials, and lab science to understand and implement robust data solutions.
Develop and maintain data models, schemas, and governance practices for structured and unstructured biomedical data.
Implement data quality checks, lineage, logging, and alerts to ensure reliability and reproducibility.
Work with cloud infrastructure teams to deploy pipelines using Azure services.
Contribute to data lake/warehouse solutions using Snowflake, Redshift, or Synapse.
Years of Exp- 6 to 8 Years
Location-Chennai
Work Mode- Work From Office -Chennai
Shift time-UK Shift time
Billrate- Ieyond this range)
Primary Skillset-Azure datafactory,Azure ,Python, Pyspark, Databricks, SQL,Azure Synapse
JD:
Experience with Azure datafactory,Azure ,Python, Pyspark, Databricks, SQL
Key Responsibilities
Design and build ETL/ELT pipelines to ingest, transform, and load data from clinical, omics, research, and operational sources.
Optimize performance and scalability of data flows using tools like Apache Spark, Databricks, or AWS Glue.
Collaborate with domain experts in genomics, clinical trials, and lab science to understand and implement robust data solutions.
Develop and maintain data models, schemas, and governance practices for structured and unstructured biomedical data.
Implement data quality checks, lineage, logging, and alerts to ensure reliability and reproducibility.
Work with cloud infrastructure teams to deploy pipelines using Azure services.
Contribute to data lake/warehouse solutions using Snowflake, Redshift, or Synapse.