Senior Data Engineer

RITWIK IT SERVICES PRIVATE LIMITED; Bengaluru; Hybrid; INR 4,500,000 - 6,500,000; Full time

Job summary

RITWIK IT SERVICES PRIVATE LIMITED in Bengaluru is seeking an experienced AWS Data Engineer with 7+ years of hands-on data engineering. The role is hybrid, with a shift from 2:00 PM to 11:00 PM IST, requiring independent contribution and client-facing interaction from Chimera Office.

You will design and optimize ETL/ELT pipelines on AWS, work with Python, SQL and PySpark, troubleshoot production issues and mentor engineers, delivering reliable data solutions and governance in collaboration with

Qualifications

• Minimum 7+ years of hands-on data engineering experience.
• Proven expertise in building scalable ETL/ELT pipelines on AWS.
• Ability to work with clients, mentor engineers and drive engineering excellence.
• Strong knowledge of performance optimisation for large-scale data workloads.

Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines on AWS-based data platforms.
• Build reusable components using Python, SQL and PySpark.
• Implement automated testing, monitoring and recovery mechanisms.
• Troubleshoot production issues and perform root-cause analysis.
• Apply data modelling, governance and security practices.
• Collaborate with platform engineering, operations and data owners.

Skills

AWS

Python

SQL

PySpark

ETL Pipelines

Tools

AWS Glue

Amazon Redshift

Amazon Athena

Spark

Job description

Hiring: AWS Data Engineer
Experience: Minimum 7+ Years
Work Mode: Hybrid (23 days per week from Chimera Office)
Shift Timing: 2:00 PM 11:00 PM IST

Role Overview

We are looking for experienced AWS Data Engineers with strong expertise in data engineering, distributed processing and performance optimisation. The ideal candidate should have hands-on experience building scalable ETL/ELT pipelines, optimising large-scale data workloads and delivering reliable data solutions on AWS.

This role requires an independent technical contributor who can work directly with clients and stakeholders, provide technical consulting, mentor engineers and drive engineering excellence.

Key Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines on AWS-based data platforms.
• Build reusable engineering components using Python, SQL and PySpark.
• Implement automated testing, monitoring, exception handling and recovery mechanisms.
• Troubleshoot production issues, perform root-cause analysis and implement preventive measures.
• Apply data modelling, metadata management, security and governance practices.
• Maintain technical documentation, operational runbooks and knowledge-transfer materials.
• Collaborate with platform engineering, operations, data owners and business stakeholders.
• Identify and resolve performance bottlenecks across data ingestion, transformation, storage and query execution.
• Optimise complex SQL queries and Spark/PySpark workloads.
• Analyse execution plans, resource utilisation, data skew, shuffle operations and memory behaviour.
• Improve partitioning, file sizing, compression, join strategies and incremental processing.
• Tune AWS Glue, Amazon Redshift, Amazon Athena and other