AWS Data Engineering Specialist
Pittsburgh, PA - On site
Skills: AWS, ETL, CI/CD, Docker, Terraform, Devops
Job Description
Extensive experience with AWS services: EMR, S3, Redshift, Glue, Lambda, Step Functions, DynamoDB, RDS, Athena, EventBridge, API Gateway, and SNS.
Expert in ETL concepts, with a strong background in AWS Glue and data pipeline orchestration.
Strong experience with PySpark and Kafka for building data streams and batch processing systems.
In-depth knowledge of data partitioning and Parquet files for efficient data storage and querying.
Strong experience with SQL, including writing complex queries, and working with databases like Redshift and Snowflake.
Proficiency in DevOps concepts, with hands-on experience in CI/CD pipelines, Docker, and Terraform.
Excellent understanding of data lake, data warehouse, and data lake house concepts.
Proven experience leading teams, mentoring engineers, and managing end-to-end technical implementations.
Experience working with Redshift Spectrum and Athena for querying large-scale data.
Understanding of security best practices for cloud data solutions, including IAM roles and policies.
Familiarity with data governance, compliance, and data quality frameworks.
Must Have
Proficiency in SQL/NoSQL and database systems (DB2, SQL Server, Snowflake, MongoDB).
Experience with ETL tools (Informatica, IICS, Talend, SSIS, Apache Airflow).
Knowledge of scripting languages (Python, Bash, Py-Spark).
Understanding of cloud data platforms like AWS Glue, S3.
Understanding of file format like JSON, Apache Parquet.
Familiarity with big data technologies (Spark, Hadoop, Kafka).
Nice to Have (Senior Roles)
Experience with real-time data processing.
Certifications in ETL tools or cloud platforms.
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