Mode : Hybrid
Essential Functions and Tasks :
Snowflake, DBT Experience is Mandatory
Onsite Experience is an added Advantage
- Lead the design, development, and maintenance of a scalable Snowflake data solution serving our enterprise data & analytics team.
- Architect and implement data pipelines, ETL / ELT workflows, and data warehouse solutions using Snowflake and related technologies.
- Optimize Snowflake database performance, storage, and security.
- Provide guidance on Snowflake best practices
- Collaborate with cross-functional teams of data analysts, business analysts, data scientists, and software engineers, to define and implement data solutions.
- Ensure data quality, integrity, and governance across the organization.
- Provide technical leadership and mentorship to junior and mid-level data engineers.
- Troubleshoot and resolve data-related issues, ensuring high availability and performance of the data platform.
Education and Experience Requirements :
4+ years of experience in-depth data engineering, with at least 3+ minimum years of dedicated experience engineering solutions in a Snowflake environment.Tactical expertise in ANSI SQL, performance tuning, and data modeling techniques.Strong experience with cloud platforms (preference to Azure) and their data services.Proficiency in ETL / ELT development using tools such as Azure Data Factory, dbt, Matillion, Talend, or Fivetran.Hands-on experience with scripting languages like Python for data processing.Strong understanding of data governance, security, and compliance best practices.Snowflake SnowPro certification; preference to the engineering course path.Experience with CI / CD pipelines, DevOps practices, and Infrastructure as Code (IaC).Knowledge of streaming data processing frameworks such as Apache Kafka or Spark Streaming.Familiarity with BI and visualization tools such as PowerBI