Top Remote Analysis Reporting Jobs in Atlanta, GA

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.

Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

Lead global data governance strategy and operating model, establish enterprise data management/MDM and data certification practices, build and lead the global governance function and steward program, drive change management and adoption across business lines, partner with cross-functional teams to resolve data risks and embed governance into workflows, and deliver measurable outcomes against the governance roadmap.

The Data Analyst will conduct full lifecycle analysis, develop reporting capabilities, monitor performance, and identify improvements in data quality and efficiency.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

Lead design and implementation of Databricks lakehouse architectures and best practices. Build and optimize Spark/Delta ETL/ELT pipelines, implement Unity Catalog governance, integrate cloud storage and services, establish CI/CD, monitor platform health, troubleshoot production issues, and provide technical leadership and architecture guidance across data engineering, analytics, ML, and security teams.

Lead development of credit and fraud strategies using data, ML models, and advanced analytics. Design A/B tests, analyze portfolio performance, conduct root-cause and ad-hoc analyses, and partner with Data Science, Product, and Engineering to implement and validate risk and fraud prevention strategies while communicating findings to stakeholders.

Design, implement, and manage in-product intercept surveys using Qualtrics; analyze user behavior and survey feedback; build and automate dashboards; integrate survey and behavioral data (e.g., Glassbox); collaborate with UX, product, and engineering teams to translate quantitative findings into actionable product improvements.

Extract, analyze, and map client data from legacy relational databases into Bloomerang systems. Export data, create and test data maps and code, document processes, report data issues, and support conversions while collaborating with engineers and project managers. Work on entry-level conversions and become a subject-matter expert on migration best practices and Bloomerang capabilities.

The Product Analyst will design experiments, analyze user behavior, and communicate insights to drive engagement and retention decisions effectively.