Data Engineer (Onsite, Lahore, Remittance Salary)
HR POD Careers
Date: 3 weeks ago
City: Lahore
Contract type: Full time
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.
- 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.
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