Top Remote Analysis Reporting Jobs in Miami, FL

The IT Senior Analyst will gather requirements, lead testing, manage integration projects, and mentor team members in a high-paced environment.

Design, optimize, and govern Komodo's Snowflake-centered data infrastructure, integrate with Databricks and adjacent stores, reduce costs and improve query performance, implement monitoring/automation, establish metadata and RBAC governance, and coach teams on best practices to meet compliance and performance SLAs.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.

Lead and mentor a distributed data engineering team while architecting and building a next-generation, largely open-source data platform. Own hands-on POCs, pipeline design, schema and query optimization, ETL reliability, observability, testing, and CI/CD. Evaluate and recommend technologies, drive migration from vendor lock-in, and translate advertising and market research needs into robust technical solutions.

As a Senior Data Scientist at Yahoo Mail, you will enhance user growth strategies via product innovation, overseeing research projects and analytics.

The Global Head of Pricing will lead pricing functions, optimize margins, develop pricing models, and ensure accurate billing while partnering with multiple teams.

Embed on the Video product team to build reusable data models, transformation layers, and pipelines (Snowflake, dbt/SQLMesh). Deliver production-ready data products (APIs, dashboards), instrumentation, experimentation infrastructure, and predictive/causal models to inform product, retention, pricing, and growth decisions.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

Build and maintain product analytics dashboards, validate and QA event tracking, translate event data into analytics-ready datasets, run funnels/cohorts/retention analyses, support A/B testing, and surface actionable product insights to Product, Growth, and Data stakeholders.