Data Engineer (Onsite, Lahore, Remittance Salary)

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 3 to 4 years of experience working as a Data Engineer in a production environment.
• Hands-on experience with AWS Redshift, AWS Data Lake, and Snowflake.
  Strong SQL skills and understanding of database concepts.
• Experience in building and maintaining data pipelines using AWS Glue, PySpark, or Airflow.
• Familiarity with data warehousing concepts, dimensional modeling, and performance tuning.
• Proficient with Python or Scala for data transformation tasks.
  Strong problem-solving and analytical skills.
• Knowledge of data privacy, security, and compliance standards is a plus.
  Experience with data cataloging tools like AWS Glue Data Catalog or Apache Hive Metastore.
• Exposure to streaming data frameworks like Kinesis, Kafka, or Spark Streaming.
• Experience integrating BI tools (e.g., Power BI, Looker, Tableau) with Redshift or Snowflake.
• Familiarity with Terraform or IaC tools for managing data infrastructure is a bonus.

Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines for ingesting data from various sources into AWS Redshift, AWS Data Lake, and Snowflake.
• Build data models and schemas optimized for analytics, reporting, and data science use cases.
• Collaborate with data analysts, product teams, and software engineers to understand data requirements and deliver clean, well-organized datasets.
• Manage and monitor scheduled jobs to ensure data reliability, quality, and consistency.
• Implement data governance, cataloging, and security practices in accordance with organizational and compliance standards.
• Optimize SQL queries and ETL jobs for performance and cost-efficiency.
• Utilize AWS services like Glue, Lambda, S3, Athena, Redshift Spectrum, etc., to support data pipeline operations.
• Perform data validation and quality checks on ingestion and transformation layers.
• Troubleshoot and debug data issues across complex data pipelines and cloud environments.