Data Engineer (Snowflake)

NexionPro Services; Bengaluru; On-site; INR 2,400,000 - 3,600,000; Full time

Job summary

NexionPro Services in Bengaluru is seeking a Snowflake Data Engineer (AI-Enabled Data Platforms) with 5–8 years of experience to design, build, and optimize scalable data pipelines and data platforms in the cloud.

You will work with Snowflake, Python, PySpark, DBT and ETL/ELT development to enable analytics and AI initiatives, ensure data quality, governance, and performance, and collaborate with data scientists and stakeholders.

Qualifications

• 5–8 years of experience in data engineering.
• Strong expertise in Snowflake, Python, PySpark, DBT, and ETL/ELT development.
• Experience building scalable data pipelines for analytics and AI use cases.
• Exposure to AI/ML-driven data platforms and data governance.

Responsibilities

• 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 for reporting, analytics, and AI initiatives.
• Create reusable and efficient data models within Snowflake.

Skills

Snowflake Data Cloud Platform

Python

PySpark

DBT

SQL

Cloud platforms

Tools

Airflow

ADF

Informatica

Job description

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

Experience: 5 to 8 Years

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

• 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.
• 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.
• 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).
• 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.