Data Engineer

JOB DESCRIPTIONS

Required Qualifications

• Upper-intermediate to fluent speaking and writing English. Able to have a real-time conversation.
• 4+ years of full-time hands-on Data Engineer experience.
• 4+ years of full-time hands-on SQL experience.
• 4+ years of full-time hands-on AWS experience.
• 3+ years of full-time hands-on Redshift/EMR/Glue experience.
• 3+ years of full-time hands-on Data modeling/Snowflake experience.
• 3+ years of full-time hands-on Python experience.
• 3+ years of full-time hands-on PySpark experience.
• Strong expertise in SQL and experience with Redshift stored procedures.
• Proficiency with AWS services, including S3, Lambda, DynamoDB, Step Functions, RDS, SNS, and SQS.
• Experience with data engineering tools such as EMR, Glue, and Redshift.
• Strong knowledge of databases, including PostgreSQL and Aurora.
• Experience with data modeling techniques, including Star/Snowflake Schema Design.
• Proficiency in Python and PySpark for data manipulation and processing.
• Knowledge of serverless architectures and experience with AWS Lambda and Step Functions.
• Strong SQL and PL/SQL skills for querying and managing data.
• Familiarity with data warehousing concepts, including Datamarts and Multi-Dimensional OLAP.
• Familiarity with data processing frameworks such as Apache Spark or Hadoop.
• Knowledge of programming languages such as Python or Java for data manipulation and automation.
• Strong understanding of data governance and best practices for data quality.
• Experience working in Agile development environments.
• Excellent problem-solving skills and attention to detail.
• Strong verbal and written communication skills, with the ability to present information clearly to stakeholders.