Data Engineer (AWS Glue / Snowflake)

Bytespoke; India; On-site; INR 1,200,000 - 2,100,000; Part time

Job summary

Bytespoke Technology Private Limited in India is seeking Junior and Senior Data Engineers with hands-on AWS Glue, Python, and AWS Data Services to design robust ETL pipelines. The role requires expertise in ETL development, AWS Glue, S3, IAM, SQL, and Snowflake is highly preferred.

You will design, implement, and optimize data pipelines, ensure data quality, and collaborate with teams to deliver scalable data solutions across on-prem and cloud environments.

Qualifications

• Hands-on experience designing ETL pipelines using AWS Glue (PySpark, Glue Jobs, Crawlers).
• Strong SQL skills for data modeling and quality checks.
• Experience with AWS data services like S3, IAM, and data orchestration workflows.

Responsibilities

• Design, develop, and maintain ETL pipelines using AWS Glue (PySpark, Glue Jobs, Crawlers, Workflows, Data Catalog).
• Build scalable data ingestion, transformation, and orchestration workflows.
• Manage data stored in Amazon S3 with lifecycle policies, encryption, versioning, and access control.
• Implement secure access using AWS IAM, roles, and cross-account permissions.
• Ensure data quality, schema validation, and error handling.
• Optimize SQL queries and support data modeling activities.
• Collaborate with cross-functional teams to deliver reliable data solutions.

Skills

AWS Glue

Python

SQL

ETL pipelines

Data Modeling

Batch processing

Event-driven processing

Tools

Snowflake

AWS S3

AWS IAM

PySpark

Job description

Bytespoke Technology Private Limited ·1 week ago

Experience: 3–6 Years (Junior) / 7–10 Years (Senior)

Location: India

Employment Type: Contract

Joining: Immediate

Job Summary

We are looking for Junior and Senior Data Engineers with strong expertise in AWS Glue, Python, and AWS Data Services to design and build scalable data pipelines. The ideal candidate should have hands-on experience with ETL development, AWS Glue, Amazon S3, IAM, SQL, and modern data engineering practices. Experience with Snowflake is highly preferred.

Key Responsibilities

• Design, develop, and maintain ETL pipelines using AWS Glue (PySpark, Glue Jobs, Crawlers, Workflows, and Data Catalog).
• Build scalable data ingestion, transformation, and orchestration workflows.
• Manage data stored in Amazon S3, including lifecycle policies, encryption, versioning, and access control.
• Implement secure access using AWS IAM, roles, and cross-account permissions.
• Ensure data quality, schema validation, and error handling.
• Optimize SQL queries and support data modeling activities.
• Collaborate with cross-functional teams to deliver reliable data solutions.

Required Skills

• 3–6 years (Junior) or 7–10 years (Senior) of Data Engineering experience.
• Strong expertise in AWS Glue (PySpark, Glue Jobs, Crawlers, Workflows, and Data Catalog).
• Advanced Python programming for ETL and data engineering.
• Hands-on experience with Amazon S3 and AWS IAM.
• Experience building metadata-driven ETL/data pipelines.
• Strong understanding of batch and event-driven data processing.
• Excellent knowledge of SQL, data modeling, and data quality practices.

Preferred Skills

• Experience with Snowflake, including COPY INTO, Snowpipe, performance optimization, and security features.
• Knowledge of cloud data platforms and modern data lake architectures.
• Experience working in Agile environments.