Key Responsibilities

Design and implement scalable data warehouse and data lake solutions using Snowflake.

Define enterprise data architecture, data models, and integration strategies.

Develop data ingestion, transformation, and ELT pipelines using Snowflake and modern ETL tools.

Optimize Snowflake performance, warehouse sizing, query tuning, and cost management.

Implement security, governance, data masking, role-based access control (RBAC), and compliance best practices.

Integrate Snowflake with cloud services, BI platforms, and enterprise applications.

Establish CI/CD pipelines and deployment automation for Snowflake environments.

Collaborate with business stakeholders to translate business requirements into technical solutions.

Provide technical leadership, architecture guidance, and mentoring to engineering teams.

Ensure data quality, reliability, scalability, and operational excellence.

Mandatory Skills

8+ years of experience in Data Engineering, Data Warehousing, or Data Architecture.

4+ years of hands-on experience with Snowflake.

Strong expertise in:

Snowflake Architecture

Snowpark

Data Modeling (Dimensional & Data Vault)

SQL Performance Tuning

ELT/ETL Design

Data Migration

Experience with cloud platforms (AWS, Azure, or GCP).

Hands-on experience with ETL tools such as dbt, Informatica, Matillion, Talend, or Azure Data Factory.

Strong SQL and Python programming skills.

Experience with Git, CI/CD, and DevOps practices.

Knowledge of Data Governance, Security, and Data Quality frameworks.

Preferred Skills

SnowPro Certification (Core/Advanced/Architect).

Experience with Kafka, Spark, Airflow, or Databricks.

Exposure to BI tools such as Power BI, Tableau, or Looker.

Experience with Agile delivery methodologies.

Knowledge of Data Mesh or Lakehouse architecture.