Aws Data Engineer

Job Description: Proeffective IT Services Private Limited

Job title: Data Engineer

Location: Remote

Terms: Full Time

Timings: Primarily IST hours with EST overlap, approximately 2:00 PM 10:00 PM IST

Number of Positions: 1

Skills: Python programming, AWS Glue, AWS S3, AWS Athena, Snowflake, ETL/ELT, Data Pipeline Development, Data Transformation, SQL, Cloud Data Engineering, Data Warehousing, Data Quality, Performance Optimization

Experience: 5 to 7 years

About us: We are committed to empowering businesses with expert IT solutions, consulting, and providing solutions tailored to meet unique needs. Our focus on quality and client satisfaction allows us to combine technology and strategy to drive your success.

If you like challenging work environment where each individual is recognized and challenged to aspire their career goals, then you are at the right place!

About the role: We are looking for an experienced Data Engineer with 5–7 years of hands-on experience in building, developing, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate should have strong expertise in Python programming, AWS Glue, AWS S3, AWS Athena, and Snowflake.

The candidate will be responsible for developing reliable ETL/ELT pipelines, integrating data from multiple sources, transforming and validating datasets, and delivering high-quality data to Snowflake and other analytical platforms.

Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Python programming and AWS services.
• Develop and maintain AWS Glue jobs and workflows for data extraction, transformation, and loading.
• Manage and optimize data storage and processing using Amazon S3 and AWS Athena.
• Develop Python-based data processing and automation solutions.
• Integrate data from multiple structured and semi-structured sources into cloud data platforms.
• Design and maintain Snowflake data pipelines, tables, views, and data models.
• Perform data transformation, cleansing, validation, and quality checks.
• Optimize data pipelines and queries for performance, scalability, and cost efficiency.
• Troubleshoot data pipeline failures and resolve production issues within defined SLAs.
• Implement monitoring, logging, error handling, and recovery mechanisms for data workflows.
• Collaborate with data analysts, architects, developers, and business stakeholders to understand data requirements.
• Participate in code reviews, testing, deployment, documentation, and production support.
• Follow data engineering best practices for security, reliability, maintainability, and scalability.
• Work effectively in a remote environment and collaborate with teams across IST and EST time zones.

Candidate Requirements:

• 5–7 years of professional Data Engineering experience.
• Strong hands-on experience with Python programming.
• Strong practical experience with AWS Glue and development of ETL pipelines.
• Hands-on experience with AWS S3 and AWS Athena.
• Strong experience working with Snowflake as a cloud data warehouse.
• Strong SQL skills and experience with data transformation.
• Good understanding of ETL/ELT, data warehousing, and data integration concepts.
• Experience handling structured and semi-structured data.
• Strong analytical and problem-solving skills.
• Experience troubleshooting production data pipelines.
• Good communication and stakeholder-management skills.
• Ability to work independently in a remote environment.
• Willingness to work primarily during IST hours with EST overlap, approximately 2 PM–10 PM IST.