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Senior Data Engineer – AWS & Snowflake
Senior Data Engineer – AWS & Snowflake
Experience: 6 to 10+ Years
Location: Islamabad, Lahore or Karachi (Hybrid)
Employment Type: Full-Time
Position Overview
We are looking for a skilled Senior Data Engineer with strong AWS and Snowflake expertise to design, develop, and optimize scalable cloud-based data pipelines and modern data warehousing solutions.
The role involves hands-on development, building high-performance ELT/ETL pipelines , and contributing to the architecture of a scalable cloud data platform . The ideal candidate has deep expertise in Snowflake data warehousing, AWS data services, and Python-based data engineering , along with a strong understanding of modern data engineering best practices . Key Responsibilities
Experience: 6 to 10+ Years
Location: Islamabad, Lahore or Karachi (Hybrid)
Employment Type: Full-Time
Position Overview
We are looking for a skilled Senior Data Engineer with strong AWS and Snowflake expertise to design, develop, and optimize scalable cloud-based data pipelines and modern data warehousing solutions.
The role involves hands-on development, building high-performance ELT/ETL pipelines , and contributing to the architecture of a scalable cloud data platform . The ideal candidate has deep expertise in Snowflake data warehousing, AWS data services, and Python-based data engineering , along with a strong understanding of modern data engineering best practices . Key Responsibilities
- Develop and maintain scalable batch and real-time data pipelines on AWS
- Build and optimize ELT/ETL pipelines using Snowflake, AWS Glue, and Spark on EMR
- Design and implement Snowflake data warehouse solutions , including schema design, clustering, and performance optimization
- Develop and manage Snowflake data models (Star/Snowflake schemas) for analytics and reporting
- Implement workflow orchestration using Apache Airflow (MWAA)
- Support serverless data processing using AWS Lambda
- Design and manage data lake architectures using Amazon S3 and Snowflake
- Implement data ingestion frameworks for structured and semi-structured data
- Optimize Snowflake query performance, storage usage, and compute costs
- Apply data governance, security, and role-based access controls using AWS DataZone and Snowflake features
- Monitor and troubleshoot data pipelines and platform issues using Amazon CloudWatch and other monitoring tools
- Collaborate with Analytics, BI, Data Science, and Business teams to enable data-driven decision-making
- Write clean, scalable, and efficient code , and participate in peer code reviews and architecture discussions
- Ensure data quality, reliability, and compliance with governance standards
- 6–10+ years of experience in Data Engineering or related roles
- 3+ years of hands-on experience designing and building data platforms on AWS
- Strong experience with Snowflake data warehouse architecture, development, and optimization
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Proficiency with AWS data services, including:
- AWS Glue
- Amazon EMR (Spark)
- AWS Lambda
- Apache Airflow (MWAA)
- Amazon EC2
- Amazon CloudWatch
- Amazon Redshift
- Amazon DynamoDB
- AWS DataZone
- Amazon S3
- Strong programming skills in Python for data engineering and pipeline development
- Advanced SQL skills with query optimization and performance tuning
- Strong understanding of data warehousing concepts and dimensional modeling (Star/Snowflake)
- Experience building scalable ETL/ELT pipelines and handling large-scale datasets
- Familiarity with Agile/Scrum delivery environments
- Strong problem-solving and analytical skills
- AWS Professional Certification (Solutions Architect / Data Analytics Specialty)
- Snowflake Certification (SnowPro Core or Advanced)
- Experience with real-time streaming technologies (Kinesis, Kafka)
- Exposure to data governance, data catalog, and metadata management tools
- Experience with CI/CD pipelines for data engineering workflows
- Knowledge of cost optimization strategies in AWS and Snowflake
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