Lead Data Engineer, AWS Data Platform & Pipelines

NorthBay Solutions LLC

Lahore

Hybrid

PKR 3,000,000 - 6,000,000

Full time

14 days+

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Job summary

NorthBay Solutions LLC in Pakistan is seeking a Lead Data Engineer (AWS Data Platform) with 5 to 8+ years of experience to design and optimize large-scale data platforms and ETL/ELT pipelines. Proficiency with PySpark, AWS Glue, EMR, Redshift, and SQL-based data warehousing is essential.

The candidate will work with a UAE-based client, collaborating with distributed teams while adhering to UAE working hours and holidays.

Qualifications

5 to 8+ years of experience in Data Engineering and Data Warehousing.
Strong hands-on experience with PySpark.
Extensive experience with AWS Glue.
Experience building and managing workloads on Amazon EMR.
Strong expertise in Amazon Redshift.
Excellent SQL development and query optimization skills.
Strong understanding of Data Warehousing concepts, dimensional modeling, and ETL/ELT processes.
Experience in performance tuning of Spark jobs, SQL queries, ETL pipelines, and data warehouse workloads.
Experience handling large-scale datasets and distributed data processing.
Strong debugging, troubleshooting, and analytical skills.

Responsibilities

Design, develop, and maintain scalable data pipelines using PySpark, AWS Glue, and Amazon EMR.
Build and optimize data ingestion, transformation, and processing frameworks for structured and semi-structured data.
Develop and maintain enterprise data warehouse solutions using Amazon Redshift.
Write complex SQL queries, stored procedures, and data transformations to support analytics and reporting requirements.
Implement ETL/ELT processes to move data efficiently across multiple systems and platforms.
Perform performance tuning and optimization of Spark jobs, ETL pipelines, SQL queries, and Redshift workloads.
Ensure data quality, integrity, security, and governance across data platforms.
Troubleshoot production issues and perform root cause analysis for data-related incidents.
Collaborate with business stakeholders, analysts, architects, and engineering teams to understand data requirements.
Participate in code reviews, technical design discussions, and best‑practice implementation.
Monitor data pipelines and proactively identify opportunities for performance improvements and automation.
Create and maintain technical documentation, data models, and operational procedures.