Principal Data Engineer – AWS Redshift & Data Platforms Job ID: 349866

HireOn LLC.; Lahore; On-site; PKR 2,232,000 - 3,348,000; Full time

Benefits offered by this job

Opportunity to work with a globally recognized client

Exposure to modern cloud data technologies

Career growth into data architecture roles

Job summary

HireOn LLC. is seeking a Principal Data Engineer to lead the development of scalable cloud-based data platforms in Lahore.

You will design high-performance data pipelines using Amazon Redshift and optimize data workflows, leveraging your expertise in AWS and Apache Airflow. This role offers hybrid work flexibility and a chance to work on impactful data initiatives within a globally recognized client.

Qualifications

• 6 to 8+ years of experience in data engineering or data platforms.
• Proven ability to design high-performance, distributed data pipelines.
• Experience with large-scale, distributed data systems.

Responsibilities

• Design and deliver high-performance data pipelines and warehouse solutions.
• Optimize processing performance and implement orchestration.
• Collaborate with cross-functional teams to drive data-driven outcomes.

Skills

Advanced expertise in Amazon Redshift

Strong hands-on experience with Apache Airflow

Proficiency in SQL

Proficiency in Python

Solid experience with AWS data ecosystems

Understanding of ETL/ELT frameworks

Experience leading engineering efforts

Strong knowledge of query optimization

Tools

Amazon Redshift

Apache Airflow

AWS services

CI/CD pipelines

Job description

Principal Data Engineer – AWS Redshift & Data Platforms

Employment Type: Full-Time | Permanent Location: Pakistan (Lahore / Karachi / Islamabad) – Hybrid

About the Opportunity

HireOn is hiring on behalf of a reputed international client seeking a Principal Data Engineer to play a pivotal role in building and scaling a next-generation cloud data platform.

This position focuses on designing and delivering high-performance data pipelines and warehouse solutions on Amazon Redshift, enabling faster analytics, improved reliability, and scalable data operations.

You will take ownership of architecting data workflows, optimizing processing performance, and implementing production-grade orchestration, while collaborating with cross-functional teams to drive data-driven outcomes.

Key Requirements (Must-Have First)

• 6 to 8+ years of experience in data engineering, data platforms, or data warehousing
• Advanced expertise in Amazon Redshift, including performance tuning, workload optimization, and MPP architecture
• Strong hands-on experience with Apache Airflow (MWAA preferred) for workflow orchestration
• Proficiency in SQL and Python for building scalable data pipelines
• Solid experience with cloud-based data ecosystems on AWS (S3, Lambda, CloudWatch, DMS)
• Deep understanding of data modeling, ETL/ELT frameworks, and large-scale data processing
• Proven ability to design high-performance, distributed data pipelines
• Experience leading engineering efforts, including code reviews, mentoring, and technical decision-making
• Strong knowledge of query optimization, parallel processing, and data pipeline efficiency

Core Technical Skills

Essential

• Amazon Redshift (Provisioned / Serverless)
• MPP data processing concepts
• Apache Airflow (MWAA)
• Advanced SQL & performance tuning
• Python for data engineering
• Data modeling & warehousing concepts

Preferred

• AWS services (S3, Lambda, DMS, Aurora PostgreSQL)
• CI/CD pipelines & Git-based workflows
• Linux/Unix environments
• Experience with large-scale, distributed data systems

What Success Looks Like

• Highly optimized and scalable data pipelines running on Redshift
• Reliable orchestration with minimal downtime and strong observability
• Efficient handling of large datasets with improved query performance
• Well-architected data platform aligned with modern engineering standards

Why Join Through HireOn

• Opportunity to work with a globally recognized client on high-impact data initiatives
• Exposure to modern cloud data technologies and large-scale systems
• Hybrid work flexibility within Pakistan
• Career growth into data architecture and platform leadership roles