Data Engineer (AWS)

Weekday (YC W21); Delhi; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A technology firm is seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines using the AWS ecosystem. Key responsibilities include developing ETL workflows and ensuring data quality. Candidates should have over 5 years of experience in data engineering and strong analytical skills. This is a full-time position based in Delhi, India.

Qualifications

• 5+ years of hands-on experience in data engineering.
• Proven expertise in the AWS ecosystem (Glue, Kinesis, Redshift, S3).
• Proficiency in SQL, Databricks, and data pipeline orchestration tools.
• Strong understanding of data analysis, data quality management, and data modeling.

Responsibilities

• Design, develop, and maintain robust data pipelines and ETL workflows using AWS.
• Work extensively with SQL and Databricks to process and analyze large datasets.
• Implement data orchestration and workflow automation using Airflow or Step Functions.
• Ensure data quality, integrity, and consistency across systems.

Skills

SQL

AWS (Glue, Kinesis, Redshift, S3)

Databricks

Data Pipeline Development

Airflow / Step Functions

Data Quality Management

Data Lake Architecture

Job description

Overview

This role is for one of our clients. Company Name: Muoro.io. Industry: Technology, Information and Media. Seniority level: Mid-Senior level. Min Experience: 5 years. Location: NCR. JobType: full-time.

We are seeking an experienced Data Engineer with deep expertise in the AWS data ecosystem to design, build, and optimize scalable data pipelines and platforms. The ideal candidate will have strong analytical skills, hands-on experience in modern data architectures, and a passion for delivering high-quality, reliable data solutions.

Base pay range

This range is provided by Weekday (YC W21). Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Key Responsibilities

• Design, develop, and maintain robust data pipelines and ETL workflows using AWS tools such as Glue, Kinesis, Redshift, S3, and Data Lake architectures.
• Work extensively with SQL and Databricks to process, transform, and analyze large datasets.
• Implement data orchestration and workflow automation using tools like Airflow or Step Functions.
• Ensure data quality, integrity, and consistency across systems through rigorous validation and monitoring practices.
• Collaborate with cross-functional teams, including data analysts and software engineers, to support data-driven decision-making.
• Optimize data storage, retrieval, and processing for scalability and performance in a cloud-native environment.

Qualifications

• 5+ years of hands-on experience in data engineering.
• Proven expertise in the AWS ecosystem (Glue, Kinesis, Redshift, S3).
• Proficiency in SQL, Databricks, and data pipeline orchestration tools.
• Strong understanding of data analysis, data quality management, and data modeling principles.
• Experience working with data lakes and modern data architectures.
• Excellent problem-solving, communication, and collaboration skills.

Core Skills

• SQL
• AWS (Glue, Kinesis, Redshift, S3)
• Databricks
• Data Pipeline Development
• Airflow / Step Functions
• Data Quality Management
• Data Lake Architecture

Seniority level

• Not Applicable

Employment type

• Full-time

Job function

• Information Technology

Industries

• Transportation, Logistics, Supply Chain and Storage

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