Senior Data Engineer

Team: Higher Ed - Elevate team produces a dynamic suite of tools and programs designed to streamline and expedite the Higher Education recruitment and admission process. Lots of data exchanges: AWS platform using Redshift as data warehouse - Dynamo of meta-data. Ideal Profile: Senior Data Engineer with strong data and native AWS skills. Tech Stack Needs Technology Some Awareness (1) Novice (2) Intermediate (3) Advanced (4) Expert (5) RedShift/SQL 4 BI Tool 3 AWS - Dynamo 1 Gen AI 3 AWS Step Function 3 AWS - Lambda 3 AWS - S3 3 AWS - SNS/SQS 3 AWS - CloudFormation 3 Python 3 node.js Development 1 JavaScript (ES6) 1 About The Opportunity As a Data Engineer on our Higher Ed Elevate team, you possess an unwavering passion for excellence in Software Engineering and a drive to transform that passion into consistent excellence in product development. You are customer-obsessed, have strong analytical and communication skills, enjoy working with native AWS services, and thrive on solving challenging business problems. You will partner with Product Owners, Architects, Developers, and other Software Engineers to help design, define, implement functional features, conduct system level validation and verify features of product development. You have an aptitude for learning and will apply this to implement advanced software engineering practices in Data Analytics within our AWS, Microservices environment to solve complex problems with a mission to release high quality software that is resilient and optimally performing. You will engage in both data and analytics reports development and quality engineering, testing and automation as a data engineer. In This Role, You Will Design & Implementation (70%) Incorporate Cloud technologies on new application development to include microservices, SQL and AWS services such as Lambda, S3, SQS, SNS, DynamoDB, Quicksight, AWS Redshift, Opensearch, and SageMaker AI Create and maintain automated functional and system tests to replicate complex real-world scenarios Develop code and our test automation suite to support security features and technical scoping, ensuring that features deliver the expected functionality with high quality Ensure that continuous integration is performed on the application source code and constantly seek to enhance the continuous integration methods of the development team to ensure extremely high quality of code Support and coordinate with other Engineers, Architects and teams such as User Experience and/or infrastructure teams Strategy & Communication (20%) Implement cloud-first architectural solutions and best practices Participate in agile scrum ceremonies (Sprint Planning, Grooming, Daily SCRUM, Demo) and contribute to team deliverables Participate in peer reviews of software engineering artifacts Team Coordination (10%) Mentor team members by designing and developing training materials to communicate the current and future product architecture Mentor technical staff by providing feedback of code and other design artifacts About You Ideally 6+ years of software development experience in a production environment Expertise writing and optimizing complex SQL queries for data extraction, transformation, and reporting (e.g., SELECT, JOIN, GROUP BY, HAVING, WINDOW functions) Expertise integrating Redshift Serverless with AWS services such as S3, Glue, Lambda, Athena, DynamoDB and Kinesis BI tools like Tableau, Quicksight, or Looker for real-time analytics and dashboards Expertise building serverless ETL pipelines with Lambda to automate data ingestion and transformation into Redshift Experience with Python required; React and Node.js nice to have Experience building event-driven cloud-based serverless applications and deploying to AWS Technical knowledge of Cloud Computing, DevOps, and Microservices Excellent communication skills with the ability to present ideas in business-friendly and user-friendly language Demonstrated ability to develop and maintain good customer working relationships Exceptional analytical, conceptual, and problem-solving abilities Proficient in designing, building, and deploying machine learning models using Amazon SageMaker Able to prioritize and execute tasks in a high-pressure environment