Snowflake+Cortex - Associate

PwC; Pune District, Gurugram District, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC is seeking a data engineer to build and maintain Snowflake and Cortex data solutions that drive client analytics and data modernization. The role focuses on developing data pipelines, transforming data, and integrating workflows across cloud platforms.

You will write efficient SQL, validate data, and support warehouse/lakehouse structures while collaborating with the team to translate business needs into technical data tasks.

Qualifications

• 2-4 years of experience building Snowflake and Cortex data solutions.
• Experience developing and maintaining data pipelines across cloud environments.
• Proficient in writing and tuning SQL queries for performance.
• Experience with data warehousing and lakehouse structures.
• Familiarity with data quality checks and troubleshooting data issues.

Responsibilities

• Develop and maintain data pipelines across cloud environments.
• Design and optimize data models for warehouse and lakehouse architectures.
• Write and tune SQL queries to improve load and query performance.
• Support data quality checks and resolve data issues across layers.
• Collaborate with teammates to translate business requirements into data tasks.
• Leverage Snowflake, Cortex, Databricks, and AWS features for scalable processing.
• Assist with orchestration using Airflow and data factory tooling.
• Learn new tools quickly while owning assigned work and delivering results.

Skills

Snowflake

Cortex data solutions

Data pipelines

SQL

Data modeling

Data validation

Airflow

Azure Data Factory

Databricks

AWS

Cloud data platforms

Tools

Apache Airflow

Azure Data Factory

Databricks

Snowflake

Job description

• 2-4 years in Building Snowflake and Cortex data solutions that support client analytics and data modernization needs
• Developing and maintaining data pipelines, transformation logic, and integration workflows across cloud-based environments
• Writing and tuning SQL queries to improve data loading, retrieval, and performance across data platforms
• Supporting data modeling, validation, and documentation activities for warehouse and lakehouse structures
• Assisting with orchestration using Apache Airflow, Azure Data Factory, or DAG-based scheduling tools
• Applying data quality checks and troubleshooting data issues across ingestion, transformation, and consumption layers
• Collaborating with team members to translate business requirements into technical data engineering tasks
• Using AWS, Databricks, and Snowflake features to support scalable and secure data processing
• Learning new tools and methods quickly while taking ownership of assigned work and delivering dependable results