Sr. AWS Data Engineer

Job Description

As a Senior AWS Data Engineer specializing in Airflow and ETL, you will be responsible for the following:- Experience in data engineering with a strong focus on ETL processes and data pipeline development.- Proficiency in using Airflow for orchestrating complex data workflows.- Extensive experience with AWS services such as S3, Lambda, Glue, and Redshift.- Strong programming skills in PySpark, with a deep understanding of distributed data processing.- Hands-on experience with Databricks for data processing and analytics.- Familiarity with additional big data technologies like Kafka, Hadoop, or Snowflake.- Knowledge of data visualization tools like Tableau, Power BI, or similar.- Experience with CI/CD tools and practices for data pipelines.- Certifications in AWS or Databricks are a plus.- Familiarity with SQL and relational databases for data extraction and manipulation.- Proven experience with data modeling, data warehousing, and building scalable data solutions.- Understanding of best practices in data management, including data governance and data security.- Strong problem-solving skills to troubleshoot complex data issues.- Excellent communication and collaboration skills to work effectively in a team environment.- Optimization of data pipelines for performance, scalability, and reliability.- Implementation of best practices for data governance, data quality, and data security.- Monitoring and troubleshooting of ETL processes to ensure data accuracy and integrity.- Working in an agile environment, actively participating in sprint planning, daily stand-ups, and retrospectives.- Documentation of data workflows, processes, and technical specifications for clear communication and knowledge sharing within the team.Qualifications:- Bachelors degree in Computer Science, Information Technology, or a related field. As a Senior AWS Data Engineer specializing in Airflow and ETL, you will be responsible for the following:- Experience in data engineering with a strong focus on ETL processes and data pipeline development.- Proficiency in using Airflow for orchestrating complex data workflows.- Extensive experience with AWS services such as S3, Lambda, Glue, and Redshift.- Strong programming skills in PySpark, with a deep understanding of distributed data processing.- Hands-on experience with Databricks for data processing and analytics.- Familiarity with additional big data technologies like Kafka, Hadoop, or Snowflake.- Knowledge of data visualization tools like Tableau, Power BI, or similar.- Experience with CI/CD tools and practices for data pipelines.- Certifications in AWS or Databricks are a plus.- Familiarity with SQL and relational databases for data extraction and manipulation.- Proven experience with data modeling, data warehousing, and building scalable data solutions.- Understanding of best practices in data management, including data governance and data security.- Strong problem-solving skills to troubleshoot complex data issues.- Excellent communication and collaboration skills to work effectively in a team environment.- Optimization of data pipelines for performance, scalability, and reliability.- Implementation of best practices for data governance, data quality, and data security.- Monitoring and troubleshooting of ETL processes to ensure data accuracy and integrity.- Working in an agile environment, actively participating in sprint planning, daily stand-ups, and retrospectives.- Documentation of data workflows, processes, and technical specifications for clear communication and knowledge sharing within the team.Qualifications:- Bachelors degree in Computer Science, Information Technology, or a related field.

Keyskills :
AWSAirflowETLGlueKafkaHadoopSnowflakeTableauPower BISQLRelational DatabasesData ModelingData WarehousingData GovernanceData SecurityCommunication SkillsAgile EnvironmentPySparkDatabricksLambdaRedshiftCICD