Full Job Description
Designation : Associate
Experience : 3 to 6 years
Job Role :
Design, build, and maintain data pipelines and platforms for a financial-services client engagement. Work hands-on across the modern data stack - increasingly AI-augmented - to deliver reliable, high-quality data solutions from source integration through analytics-ready models.
Responsibilities :
Build and optimize data pipelines and ELT workflows across concurrent workstreams.
Develop solutions on Snowflake, dbt, Databricks, and Azure.
Design data models and write performant SQL, Python, and PySpark for transformation and remediation.
Implement engineering best practices - CI/CD, data quality checks, and orchestration.
Support migration and re-architecture efforts (e.g., SQL-to-dbt), leveraging AI-assisted and agentic tooling to accelerate delivery.
Apply AI/LLM-based tools in day-to-day engineering - code generation, automated migration, and productivity workflows.
Required Skills:
Hands-on data engineering experience across the modern data stack.
Strong proficiency in Snowflake, dbt, SQL, Python, and PySpark.
Experience with cloud data platforms (Azure) and orchestration tooling.
Familiarity with CI/CD and data quality practices.
Exposure to AI-assisted development or agentic tooling a plus.
