• Working with multiple stakeholders to provide quantitative support. • Define metric rules and logic, deliver tables and reports. • Model business scenarios and solve a wide range of business problems. • Create new pipelines from scratch, merging financial and ERP data sets. • Engineering foundational table resources using Google Cloud Platform (GCP): BigQuery, Dataform, LookML, Dataplex, etc. • Develop pipelines, metrics, tools, and analyses for strategic decision-making.

• Design, build, and maintain robust ETL/ELT pipelines across AWS-native data environments • Own Airflow orchestration — scheduling, dependencies, retries, alerting, and operational support • Develop analytics-ready data models in dbt, using modular, warehouse-first transformation patterns • Work confidently across S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing • Contribute to the roadmap and potential migration toward Snowflake as a future warehouse • Write clean, maintainable Python for pipeline logic, scripting, and lightweight engineering tasks • Embed data quality, testing, and observability into every pipeline — not as an afterthought • Engage directly with client stakeholders: gather requirements, present solutions, and advise on trade-offs • Partner with analysts, product teams, and other engineers in a distributed, remote-first setup

• Design, build, and maintain robust ETL/ELT pipelines across AWS-native data environments • Own Airflow orchestration — scheduling, dependencies, retries, alerting, and operational support • Develop analytics-ready data models in dbt, using modular, warehouse-first transformation patterns • Work confidently across S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing • Contribute to the roadmap and potential migration toward Snowflake as a future warehouse • Write clean, maintainable Python for pipeline logic, scripting, and lightweight engineering tasks • Embed data quality, testing, and observability into every pipeline — not as an afterthought • Apply sound version control, code review, and CI/CD practices to data workloads • Engage directly with client stakeholders: gather requirements, present solutions, and advise on trade-offs • Partner with analysts, product teams, and other engineers in a distributed, remote-first setup • Contribute to architectural reviews, retrospectives, and continuous improvement of platform practices

• Partner closely with Finance/Music Ops/Acquisitions, and other business stakeholders to understand reporting needs, data gaps, and analytical requirements • Collaborate with internal data teams to translate business questions into scalable, well-modeled analytics ready data solutions • Develop, optimize, and maintain complex SQL queries and reporting tables, including recommending improvements to existing SQL data models • Analyze & integrate data from disparate data sets to develop niche reporting tables and generate meaningful insights • Apply software engineering best practices to analytics code (version control, testing, continuous integration) • Participate in code reviews, optimize SQL for performance (including Sigma-specific optimization), maintain data documentation & definitions • Other duties as assigned