Snowflake Data Engineer

Job Summary :

We are seeking a highly skilled Snowflake Data Engineer with strong expertise in Snowflake, Python, PySpark, DBT, and ETL/ELT development. The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines, transforming data for analytics and AI use cases, and supporting modern cloud-based data platforms.

Key Responsibilities :

Data Engineering & Development :

- Design, develop, and maintain scalable ETL/ELT pipelines using Snowflake, Python, PySpark, and DBT.

- Develop robust data ingestion frameworks for structured, semi-structured, and unstructured data.

- Build and optimize data transformation workflows to support reporting, analytics, and AI initiatives.

- Create reusable and efficient data models within Snowflake.

Snowflake Data Platform :

- Design and implement Snowflake architectures and data warehouse solutions.

- Develop Snowflake objects including databases, schemas, tables, views, streams, tasks, and stored procedures.

- Implement performance tuning strategies to optimize query execution and warehouse utilization.

- Manage data loading using Snowpipe, external stages, and cloud storage integrations.

DBT Development :

- Develop and maintain DBT models, macros, tests, and documentation.

- Implement data quality and validation checks using DBT.

- Build scalable ELT frameworks aligned with industry best practices.

- Create and maintain DBT lineage and transformation documentation.

Python & PySpark :

- Develop data processing frameworks using Python and PySpark.

- Build scalable data transformation and validation processes.

- Handle large-volume data processing in distributed environments.

- Implement data cleansing, enrichment, and aggregation logic.

AI & Advanced Analytics Enablement :

- Support AI/ML initiatives by preparing and engineering data for model development.

- Build data pipelines that serve machine learning and Generative AI applications.

- Work with data scientists and AI teams to deliver optimized datasets for training and inference.

- Understand AI concepts such as feature engineering, vector databases, LLM integration, and AI-driven analytics.

Data Quality & Governance :

- Implement data quality frameworks, reconciliation processes, and automated validations.

- Monitor data reliability, completeness, and consistency.

- Ensure compliance with data governance and security standards.

- Document data lineage, transformation logic, and business rules.

Collaboration :

- Work closely with Data Architects, Data Scientists, Analysts, Product Owners, and Business Stakeholders.

- Participate in Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.

- Support production deployments, troubleshooting, and root-cause analysis.

Required Skills :

Technical Skills :

- Strong hands-on experience with Snowflake Data Cloud Platform.

- Strong experience in Python development.

- Expertise in PySpark for large-scale data processing.

- Hands-on experience with DBT (Data Build Tool).

- Extensive experience in ETL/ELT pipeline development.

- Advanced SQL development and query optimization skills.

- Experience working with cloud platforms such as AWS, Azure, or GCP.

- Knowledge of Git-based version control systems.

AI & Data Science Awareness :

- Understanding of AI/ML lifecycle and data preparation.

- Knowledge of Generative AI concepts.

- Exposure to LLMs, embedding models, vector databases, or AI-powered analytics solutions.

- Experience supporting AI data pipelines is preferred.

Preferred Qualifications :

- Experience with Airflow, ADF, Informatica, or other orchestration tools.

- Snowflake certification preferred.

- Experience implementing Data Vault, Star Schema, or Dimensional Modeling.

- Experience with CI/CD pipelines and DevOps practices.

- Exposure to Power BI, Tableau, or other BI tools.

- Knowledge of Data Governance and Data Quality frameworks.

Soft Skills :

- Strong analytical and problem-solving abilities.

- Excellent communication and stakeholder management skills.

- Ability to work independently in a fast-paced environment.

- Strong documentation and presentation skills.

- Collaborative mindset with experience working in cross-functional teams.

Skills

Data Engineering, Snowflake DB, Python, AWS, Data Warehousing, SQL, Apache Airflow, PySpark, Data Build Tool, ETL, Data Pipeline