Senior Associate

Position Summary

We are seeking a hands-on Project Lead with 4-6 years of experience in designing, developing, and deploying data integration pipelines using Python/PySpark, AWS Glue, and Databricks, with strong proficiency across AWS services including EC2, S3, IAM, Athena, and VPC. The ideal candidate brings deep expertise in Spark-based distributed computing, Databricks components (Databricks certified woudl be preferred) and the ability to code across R/Python/Scala/SQL while performing performance tuning and executor management. This role requires someone who can lead by example — independently driving technical delivery while mentoring and supervising 1-2 team members, with awareness of ML algorithms, data modelling frameworks (CRISP-DM), and a pharma domain background being a strong added advantage.

Job Responsibilities

• Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies


• Be a part of large delivery teams working on advanced projects when expert assistance is required.


• Deliver advanced Data Science capabilities to businesses in a meaningful manner through successful proof-of-concept solutions, and later smoothly transition the proof-of-concept into production.


• Create LLD/STM documents, develop, test, and deploy data integration processes using Python/PySpark on AWS/Azure platform preferably using AWS Glue /Databricks - Collaborate with onshore/offshore lead designers, analyze LLD/STM, translate & apply business rules to data transformations


• Expertise Data Management principles. Experience in setting up ingestion, data processing- versioning, labelling, curating.


• Building ETL / data warehouse transformation processes and implementing Data lake project. Solutioning with large data sets, data processing at scale involving structured, semi-structured, and unstructured data formats.


• Data connectors for APIs, Kafka, batch processing.


• Managing Descopes involving Databricks, and various AWS components

Education

Work Experience

• Minimum of 4-6 years develop, test, and deploy data integration processes using Python/PySpark on AWS platform preferably using AWS Glue Databricks.


• Deep understanding of architecture and work experience on AWS Databricks, hands-on programming with Data Frames, Python, Scala.


• Good experience of Databrick components like Notebook, workspace, MLFlow and security management, creating dashboards, importing packages, DBFS, ML Flow, widgets and jobs in Databricks

• Familiar with cluster management, capacity & cost control in Databricks. Familiar with user & group access management and control


• Is aware of the overall architecture and UI


• Good experience of the notebook access management,

• Can code in R/Python/Scala/SQL


• 2-3 years of experience on Spark with Scala/Python/Java. Good experience of the distributed computing paradigm and various concepts in Spark


• Can perform performance tuning, executor management etc.


• Thorough knowledge of EC2, IAM, S3, VPC, Athena and Glue


• Is aware of the security and process design in AWS environment

• Is aware of the different phases involved in data modelling (CRISP-DM Model)


• Is aware of relevant modelling exercise to be performed (Forecasting, Clustering, Association, Classification etc.)

Behavioural Competencies

Technical Competencies

Skills