Posted on: 24/08/2026
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.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1665670