Software Engineer II

LED FastStart•New Orleans, LA

11d•Remote

About The Position

Develop real time data pipelines and solve big data problems utilizing modern technologies like Spark, Python, Java/Scala, SQL, and AWS cloud environment. Write reliable, maintainable, well-documented code that will scale to support millions of respondents. Create and maintain optimal data pipeline architecture. Execute the full software development life cycle as part of an Agile team. Collaborate with Product Managers to refine and modify requirements. Follow established design paradigms and design patterns. Utilize abilities in unit testing and integration testing. Participate in the on-call rotation to monitor shipped features for success and issues. Support the business teams and product managers in data extracts and data analysis. Demonstrate proficiency in developing software for the user interface, business logic, data modeling and systems, and component integration. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Perform pull requests reviews and CI/CD pipeline integration. Develop and manage end-to-end ETL pipelines for both real-time and batch processing, ensuring the secure and efficient migration of large-scale datasets from MSSQL environments to cloud-based data warehouses. Engineer robust streaming architecture using SNS, Kinesis Data Streams, and Kinesis Data Analytics to enable real-time insights and schema-validated ingestion, ensuring high-quality data delivery. Utilize the following tools and technologies: Github, SQL, REST APIs, and Jira.

Requirements

Master's degree or foreign equivalent degree in Computer Science, Technology Management, or closely related field.
At least 1 year (12 months) of experience in a software engineer position or closely related occupation.
At least 1 year (12 months) of experience with performing pull requests reviews and CI/CD pipeline integration.
At least 1 year (12 months) of experience developing and managing pipelines ensuring secure and efficient migration of large-scale datasets.
At least 1 year (12 months) of experience writing and optimizing complex, performance-oriented SQL queries.
At least 1 year (12 months) of experience engineering advanced data features/architectures to ensure high-quality data delivery.
At least 1 year (12 months) of experience utilizing the following tools and technologies: Github, SQL, REST APIs, and Jira.

Responsibilities

Develop real time data pipelines and solve big data problems utilizing modern technologies like Spark, Python, Java/Scala, SQL, and AWS cloud environment.
Write reliable, maintainable, well-documented code that will scale to support millions of respondents.
Create and maintain optimal data pipeline architecture.
Execute the full software development life cycle as part of an Agile team.
Collaborate with Product Managers to refine and modify requirements.
Follow established design paradigms and design patterns.
Utilize abilities in unit testing and integration testing.
Participate in the on-call rotation to monitor shipped features for success and issues.
Support the business teams and product managers in data extracts and data analysis.
Demonstrate proficiency in developing software for the user interface, business logic, data modeling and systems, and component integration.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Perform pull requests reviews and CI/CD pipeline integration.
Develop and manage end-to-end ETL pipelines for both real-time and batch processing, ensuring the secure and efficient migration of large-scale datasets from MSSQL environments to cloud-based data warehouses.
Engineer robust streaming architecture using SNS, Kinesis Data Streams, and Kinesis Data Analytics to enable real-time insights and schema-validated ingestion, ensuring high-quality data delivery.
Utilize the following tools and technologies: Github, SQL, REST APIs, and Jira.