Live opening · Posted 9 days ago
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About the role
Description supplied by the original job listing.
We are looking for an experienced Snowflake Data Engineer with strong expertise in Snowflake, Advanced SQL, DBT, Data Modeling, and Python/Shell scripting. The candidate will be responsible for designing scalable data pipelines, developing data models, optimizing Snowflake workloads, ensuring data quality, and integrating Snowflake with cloud platforms and analytics tools.
Key Responsibilities
Design and develop scalable ETL/ELT data pipelines for ingesting, transforming, and loading data into Snowflake.
Design conceptual, logical, and physical data models based on business requirements.
Develop fact and dimension tables, Star Schema, Snowflake Schema, and other dimensional models.
Develop and maintain transformation workflows using DBT (Data Build Tool).
Write complex and optimized SQL queries for data transformation, reporting, and analytics.
Perform Snowflake performance tuning using clustering, query optimization, caching, warehouse sizing, and resource monitoring.
Integrate Snowflake with AWS/Azure cloud services, storage platforms, APIs, and external data sources.
Develop automation using Python, Shell scripting, or similar scripting languages.
Implement data validation, cleansing, monitoring, and reconciliation processes to ensure data quality.
Troubleshoot data pipeline failures, query performance issues, and integration problems.
Integrate Snowflake with BI tools such as Tableau, Power BI, and Looker.
Implement Snowflake security and governance practices including RBAC, data masking, encryption, and access controls.
Collaborate with data scientists, analysts, developers, and business stakeholders to deliver data solutions.
Maintain technical documentation covering data models, pipelines, processes, and best practices.
Participate in CI/CD and DevOps practices for data engineering workflows.
Stay updated with new Snowflake features and modern data engineering technologies.
Mandatory Skills
Strong hands-on experience with Snowflake
Strong Advanced SQL skills
Hands-on experience with DBT / Data Build Tool
Strong understanding of Data Warehousing and Dimensional Modeling
Experience with Star Schema / Snowflake Schema
Experience designing Fact and Dimension tables
Proficiency in Python, Shell scripting, or similar
Experience with AWS or Azure and Snowflake integration
Strong knowledge of Snowflake performance tuning and optimization
Good understanding of data quality, security, and governance
Good to Have
SnowPro Core / SnowPro Advanced certification
Kafka or Spark Streaming experience
Snowflake integration with ML/AI platforms
Snowflake cost optimization and workload management
CI/CD and DevOps experience
Advanced security features such as data masking and row-level security
Experience with Tableau, Power BI, or Looker
Experience mentoring junior engineers
Required Competencies
Strong analytical and problem-solving skills
Good communication skills
Ability to troubleshoot complex data and pipeline issues
Ability to work effectively with technical and business stakeholders
Strong ownership and collaboration skills
Ability to document and explain technical solutions clearly
Ideal Candidate Profile
6–8 years of relevant experience with strong hands-on expertise in:
Snowflake + DBT + Advanced SQL + Dimensional Data Modeling + Python/Shell + AWS/Azure
Candidates should have demonstrated experience designing production-grade data pipelines and data models in Snowflake, along with hands-on performance optimization and data engineering best practices.
Skills: shell scripting,data models,dbt,snowflake,python
Work arrangement
No
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