Data Engineer ( AWS )

Letitbex AI; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

LetitbexAI is seeking an experienced Data Engineer to join our fast-growing team in India. You will design and optimize robust ETL/ELT pipelines, work with Spark, Python, PySpark, and SQL, and contribute to scalable data platforms on AWS.

The ideal candidate has 7–12 years of hands-on AWS experience across S3, Glue, Redshift, EMR, Lambda, IAM, and CloudWatch, plus data lakes, warehousing, and modeling expertise. Agile/Scrum workflow and strong problem-solving are essential.

Qualifications

• 7–12 years in Data Engineering.
• Strong hands-on experience with AWS (must have).
• Advanced Python, PySpark, and SQL.
• Experience designing and developing ETL/ELT pipelines.
• Hands-on Apache Spark experience.
• Expertise in AWS services S3, Glue, Redshift, EMR, Lambda, IAM, and CloudWatch.
• Data Lakes, Data Warehousing, and Data Modeling.
• Strong skills in query optimization, pipeline performance tuning, and troubleshooting.
• Excellent analytical thinking and ability to resolve complex production issues.
• Version control with Git. Working in Agile/Scrum environments.

Skills

Data Engineering

Python

PySpark

SQL

ETL/ELT pipelines

Apache Spark

Git

Agile/Scrum

Troubleshooting

Analytics

Tools

AWS S3

AWS Glue

AWS Redshift

AWS EMR

AWS Lambda

AWS IAM

AWS CloudWatch

Job description

LetitbexAI is a fast-growing AI-driven technology company focused on building intelligent, scalable, and enterprise-grade solutions. We work at the intersection of AI, data engineering, cloud, and business transformation, helping organizations unlock real value from artificial intelligence.

Experience: 7-12 Years

Notice Period: Can be considered up 15 Days

Mandatory Requirements Experience:

7–12 years in Data Engineering. Cloud Platform: Strong hands-on experience with AWS (must have).

Programming: Advanced Python, PySpark, and SQL. Data Engineering: Strong expertise in designing and developing ETL/ELT pipelines.

Big Data: Hands-on experience with Apache Spark.

AWS Services: Expertise in S3, Glue, Redshift, EMR, Lambda, IAM, and CloudWatch.

Data Architecture: Experience with Data Lakes, Data Warehousing, and Data Modeling.

Performance: Strong skills in query optimization, pipeline performance tuning, and troubleshooting.

Problem Solving: Excellent analytical thinking and ability to resolve complex production issues. Version Control: Experience with Git. Working Model: Experience in Agile/Scrum environments.