Job Description

Software Engineer, Associate

Department: Development

Employment Type: Full Time

Location: Remote

Description

We are looking for a Software Engineer, Data & Analytics to join our Product Development team. In this role, you will own and enhance the data platform that enables our business and customers to understand performance and make data-driven decisions.

You will manage and optimize our Amazon Redshift environment, develop impactful Amazon QuickSight dashboards, and build AI-driven workflows that transform raw data into timely, actionable insights.

A Typical Day in the Life Includes

• Administering and optimizing Amazon Redshift clusters, including schema design, distribution and sort keys, workload management, query tuning, and access control.
• Building and maintaining QuickSight dashboards and datasets, including SPICE refreshes, calculated fields, and row-level security.
• Designing and operating AI-driven workflows, including LLM-powered summarization, anomaly detection, automated reporting, and natural-language querying of data.
• Partnering with Product, Operations, and business stakeholders to translate business questions into clearly defined metrics and reporting solutions.
• Monitoring data quality and freshness in Redshift and collaborating with Data Engineering teams to resolve upstream issues.
• Documenting data models, metric definitions, dashboards, and workflows to ensure they are trusted, reusable, and maintainable.
• Working in an Agile environment, including Scrum/Kanban, and contributing to technical decisions around the data and AI technology stack.

Basic Qualifications

• Strong SQL skills, including complex queries, window functions, and performance tuning.
• Hands-on experience administering and optimizing Amazon Redshift.
• Experience developing dashboards and datasets using Amazon QuickSight, or comparable BI tools such as Power BI or Tableau.
• Proficiency in Python for data processing, automation, and scripting.
• Experience with AWS analytics services, particularly S3, Lambda, and IAM.
• Strong understanding of data modeling concepts, including dimensional modeling and star/snowflake schemas.
• Experience with version control using Git.

Preferred Qualifications

• Experience working with LLMs or Generative AI services, such as Amazon Bedrock.
• Knowledge of prompt design, Retrieval-Augmented Generation (RAG), and methods for evaluating AI output quality.
• Experience with Infrastructure as Code tools such as Terraform, AWS CDK, or CloudFormation.
• Understanding of CI/CD practices.
• Familiarity with data governance, privacy, and security practices within analytics environments.
• Experience supporting analytics solutions in a SaaS or multi-tenant environment.