About this role
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 .