AWS Data Engineer

Overview

Join our dynamic team as an AWS Data Engineer and become a vital driver of our data-driven initiatives! In this role, you will harness the power of cloud technology, big data systems, and advanced data management tools to design, develop, and optimize scalable data pipelines and architectures. Your expertise will enable us to unlock insights from complex datasets, support business intelligence efforts, and facilitate innovative analytics solutions. If you thrive in a fast-paced environment where your technical skills directly impact strategic decision-making, this is the opportunity for you!

Responsibilities

• Design, develop, and maintain robust ETL (Extract, Transform, Load) pipelines using AWS services such as AWS Glue, Lambda, and S3 to ensure seamless data flow across systems.
• Build and optimize data models and schemas for data warehouses utilizing dimensional modeling techniques to support efficient querying and reporting.
• Collaborate with cross-functional teams to integrate diverse data sources including SQL databases like Microsoft SQL Server and Oracle, as well as big data platforms such as Hadoop, Spark, and Apache Hive.
• Develop scalable data solutions leveraging cloud databases like Azure Data Lake and cloud-based data warehousing systems to support enterprise analytics initiatives.
• Implement best practices for data management integration, query management, and data warehousing design to ensure high performance and reliability.
• Utilize programming languages such as Python and Java for software development tasks related to data engineering workflows.
• Support business intelligence tools like Looker by preparing clean datasets for analysis and visualization purposes.
• Contribute to agile development cycles by participating in sprint planning, code reviews, and continuous improvement efforts.

Experience

• Proven experience working with AWS cloud services including S3, Lambda, Glue, Redshift or similar cloud-based data warehouses.
• Strong background in big data systems such as Hadoop ecosystem components (HDFS, Hive), Spark, and related technologies.
• Extensive knowledge of SQL databases including Microsoft SQL Server, Oracle, and cloud databases like Azure Data Lake or similar platforms.
• Hands-on experience designing data models using dimensional modeling techniques for efficient data warehousing.
• Proficiency in ETL pipeline development utilizing tools like Talend or Informatica is highly desirable.
• Skilled in programming languages such as Python, Java, Bash (Unix shell), Shell Scripting or VBA for automation and scripting tasks.
• Familiarity with business intelligence tools like Looker or equivalent visualization platforms for reporting purposes.
• Strong analysis skills with the ability to interpret complex datasets and communicate insights effectively within an agile environment.

Embark on a journey where your technical expertise fuels innovative solutions! We are committed to fostering a collaborative atmosphere that values continuous learning and professional growth—empowering you to make a meaningful impact through cutting-edge cloud-based data engineering practices!

Pay: $115,973.20 - $139,666.64 per year

Work Location: In person