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Lead Snowflake Data Engineer

EPAM Systems
Posted on
EPAM Systems logo

Experience
8 - 13 yrs
Salary (CTC)
₹15L - ₹30L
Job Location
Hyderabad, India
Vacancy
1
Designation
Snowflake Data Engineer
Job Type
ONSITE

Job Description

Job title: Lead Snowflake Data Engineer

Primary Skill: Snowflake (Snow SQL, Snow PLSQL and Snowpark, SNowflake DBT)

Location: Coimbatore


Key Skills:

Main Technology Focus

  • Snowflake with strong hands-on experience inDBT
  • AWS, Python, SQL, PySpark
  • Data engineering set-up with strong programming skills

Requirements:

  • Looking for engineer for information warehouse
  • Warehouse is based on AWS/Azure, DBT, Snowflake.
  • Strong programming experience with Python.
  • Experience with workflow management tools like Argo/Oozie/Airflow.
  • Experience in Snowflake modelling - roles, schema, databases
  • Experience in data Modeling (Data Vault).
  • Experience in design and development of data transformation pipelines using the DBT framework.
  • Experience with Cloud providers, preferably AWS
  • The warehouse must be scalable, secure and well performant. The solution should be reusable and support future use cases.
  • This will be used as storage layer for the platform
  • Essential part of the warehouse is integration with monitoring and observability capabilities.

Responsibilities:

  • Snowflake Data Modeling: Design and implement scalable Snowflake data models, optimized for data ingestion and analytics requirements.
  • ETL Pipeline Development: Build and maintain robust ETL pipelines to integrate data from multiple sources into Snowflake, ensuring data integrity and consistency.
  • Performance Optimization: Optimize Snowflake usage and storage, tuning query performance and managing data partitions to ensure quick, reliable access to data.
  • Data Security & Governance: Implement best practices in data security, role-based access control, and data masking within Snowflake to maintain compliance and data governance standards.
  • Automation & Workflow Management: Utilize tools such as dbt and Apache Airflow to schedule data processing and automate pipeline monitoring.
  • Collaboration & Troubleshooting: Partner with data scientists, business analysts, and other stakeholders to address complex data challenges and troubleshoot Snowflake-related issues effectively.
  • Documentation & Reporting: Develop comprehensive documentation for data structures, ETL workflows, and system processes to ensure transparency and knowledge sharing within the team.