Data Engineer (Snowflake)

NexionPro Services · Bengaluru, India

Job Title: Snowflake Data Engineer (AI-Enabled Data Platforms)

Experience: 5 to 8 Years

Location: Bangalore/Chennai

Employment Type: Full-Time

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.

The candidate should have a strong understanding of data engineering best practices, data warehousing concepts, performance optimization, and exposure to AI/ML-driven solutions.

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.

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.