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Snowflake AWS Engineer

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Hybrid

Snowflake AWS Engineer

InfoCepts

Snowflake AWS Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonData ScienceAWS LambdaSnowflakeGitData AnalysisAWSCRMWorkdayTalendComplianceAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

4 September 2026

What they need


Position: Data Engineer- Snowflake AWS Glue

Purpose of the Position: To design, develop, and maintain scalable data pipelines and models in Snowflake for retail operations, enabling accurate reporting and analytics across customer, sales, inventory, and workforce domains.

Location: Pune/ Bangalore/Chennai/ Nagpur(hybrid)

Key Result Areas and Activities:

  • Data Pipeline Development: Integrate data from different sources like MMS, CRM, Workday, Courion, and other sources via S3 files, APIs, or direct staging in Snowflake.
  • ETL Development: Build and optimize ETL workflows using Talend , AWS Glue and SQL stored procedures.
  • Data Modeling: Create and maintain Snowflake tables and layered views for business consumption.
  • Collaboration: Work closely with data analysts, business stakeholders, and regulatory teams to understand data needs and deliver solutions.
  • Performance Optimization: Ensure efficient query performance and cost-effective data processing in Snowflake.
  • Documentation & Governance: Maintain clear documentation of data models, transformations, and lineage to support audit and compliance requirements.

Essential Skills

  • Strong hands-on experience with Snowflake (data warehousing, performance tuning, security).
  • Strong SQL skills with stored procedure development.
  • Solid understanding of SQL and advanced query optimization techniques.
  • Strong experience in Python development for data engineering, automation, and ETL/ELT pipeline development.
  • Hands-on experience in designing, developing, and maintaining AWS Glue pipelines, including Glue Jobs, Crawlers, Data Catalog, and workflow orchestration.
  • Experience building scalable data integration and transformation solutions using AWS services such as S3, Glue, Lambda, and Step Functions.
  • Familiarity with version control (Git) and CI/CD workflows.
  • Experience with cloud platforms (AWS, Azure, or GCP), with strong preference for AWS.
  • Knowledge of data pipeline monitoring, performance optimization, and troubleshooting in cloud-based data environments.

Qualification:

  • Experience: 5+ years in data engineering, with at least 2 years in Snowflake.
  • Education: Bachelors or master’s degree in computer science, Data Science, Bioinformatics, or related field.

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