Job Summary
We are seeking an experienced
AWS Data Engineer with 6+ years of experience in building scalable data pipelines, designing data architectures, and working with cloud-based data platforms. The ideal candidate will have strong expertise in
AWS services, ETL development, data warehousing, and big data technologies to support advanced analytics and business intelligence initiatives.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using AWS cloud services.
- Build and optimize ETL/ELT processes to ingest data from multiple sources.
- Develop and manage data lakes and data warehouses on AWS.
- Work with large-scale datasets and ensure data quality, reliability, and performance.
- Implement data transformation and integration solutions using tools such as AWS Glue or Apache Spark.
- Collaborate with data scientists, analysts, and business teams to deliver high-quality datasets.
- Optimize queries and improve performance in Amazon Redshift, Athena, or other AWS data services.
- Implement data governance, security, and compliance standards.
- Monitor and troubleshoot data pipelines and workflows.
- Automate data processes using Python, SQL, and scripting tools.
Required Skills- 6+ years of experience in Data Engineering or Big Data development.
- Strong experience with AWS services, such as:
- Amazon S3
- AWS Glue
- Amazon Redshift
- AWS Lambda
- Amazon EMR
- Amazon Athena
- AWS Step Functions
- Strong SQL and Python programming skills.
- Experience building ETL pipelines and data workflows.
- Knowledge of data modeling, data warehousing, and big data concepts.
- Experience with Apache Spark / PySpark.
- Familiarity with workflow orchestration tools like Apache Airflow.
- Understanding of CI/CD and DevOps practices.
Skills: aws,etl,athena,amazon redshift,apache spark
