You will work on scalable data solutions, supporting analytics, reporting, and business intelligence for a US-based product company in the financial domain.

Key Responsibilities :

- Develop and maintain ETL / ELT data pipelines

- Work with AWS services (especially AWS Glue, S3) for data ingestion and processing

- Build PySpark / Spark SQL pipelines for large-scale data processing

- Perform data transformation, validation, and optimization

- Work with Databricks (preferred) for data engineering workflows

- Write and optimize complex SQL queries

- Support data warehousing and reporting use cases

- Collaborate with cross-functional teams (Product, Analytics, Engineering)

- Troubleshoot data pipeline issues and ensure data quality

Required Skills :

- Strong experience in Python / PySpark

- Good knowledge of SQL (advanced queries, joins, optimization)

- Hands-on experience with AWS (Glue, S3, basic services)

- Experience in ETL / ELT pipeline development

- Understanding of data warehousing concepts

- Exposure to Databricks (preferred)

- Basic understanding of data governance and data quality

Preferred Skills :

- Experience in financial domain / fintech products

- Exposure to Tableau / Power BI

- Knowledge of Spark SQL and Delta Tables

- Understanding of batch and real-time data processing

Benefits :

- Competitive compensation

- Opportunity to work on AI-powered data platforms

- Exposure to US-based clients and modern tech stack

- Strong learning and career growth opportunities

- Collaborative and product-driven environment