Business Intelligence & Data Analyst

CAI•Miramar, FL

1d•$35 - $40•Onsite

About The Position

CAI is seeking a Business Intelligence & Data Analyst to support business intelligence, data analytics, cloud data migration, and reporting initiatives. The role works closely with Product and Engineering teams to connect and organize large datasets, migrate legacy data to the cloud, create and maintain reports, and translate complex business needs into actionable insights. The position is a contract role based onsite in Miramar, Florida, with direct employment through CAI. The position does not offer work authorization sponsorship now or in the future. The analyst will plan and execute cloud migrations of legacy data, host and manage datasets in Databricks, build and optimize SQL and Python workflows, and support data engineering pipelines. The role also covers data quality, dataset transformation, troubleshooting, Power BI and Excel reporting, and stakeholder liaison work. Operational data may be used to inform decisions such as staffing levels, room-cleaning requirements, food supply planning, and resource allocation.

Requirements

3–5 years of experience in data analysis, business intelligence, or a similar role.
Bachelor’s degree in Data Science, Computer Science, Information Systems, Statistics, Business, or a related field, or equivalent professional experience.
Advanced SQL proficiency, including complex joins, CTEs, window functions, and query optimization.
Strong experience creating and maintaining Power BI reports and dashboards, including DAX, data modeling, and row-level security.
Advanced Excel skills, including pivot tables, Power Query, complex formulas, and data modeling.
Working proficiency in Python for data manipulation, automation, and analysis, including pandas and NumPy.
Advanced hands-on Databricks experience, including organizing and hosting datasets, building notebooks, and connecting external data sources and BI tools.
Experience connecting and integrating multiple databases and large datasets using Databricks.
Proven experience migrating legacy data to cloud environments, including migration planning, execution, reconciliation, and validation.
Demonstrated experience cleaning, transforming, standardizing, and organizing large, complex datasets.
Ability to read and understand existing queries and develop queries for business and reporting needs.
Experience creating and maintaining recurring BI reports and analytics.
Strong communication skills and ability to serve as a liaison between technical and non-technical stakeholders.

Nice To Haves

Experience with hospitality, hotel operations, guest experience, housekeeping, staffing, or similar operational datasets.
Experience with Delta Lake, Unity Catalog, or Databricks SQL.
Familiarity with Azure, AWS, or GCP.
Exposure to ETL/ELT and orchestration tools such as Azure Data Factory, Airflow, or dbt.
Understanding of star schemas, dimensional modeling, and data governance concepts.
Experience working in an Agile product development environment.
Databricks Certified Data Analyst Associate, Databricks Certified Data Engineer Associate, Microsoft PL-300, or similar certification.

Responsibilities

Plan and execute migration of legacy data sources and databases to the cloud while maintaining data accuracy, completeness, and minimal business disruption.
Validate migrated data through reconciliation checks and document migration processes and data lineage.
Identify and support the retirement of redundant or outdated legacy data assets.
Host, organize, and manage large datasets in Databricks, including tables, schemas, workspaces, and notebooks.
Connect Databricks with upstream and downstream databases, applications, and BI tools.
Build and optimize queries, notebooks, and workflows using SQL and Python.
Partner with Data Engineering teams on pipeline design, performance tuning, and data access.
Clean, transform, standardize, and organize large datasets from multiple sources.
Establish and maintain data quality checks, naming conventions, and supporting documentation.
Troubleshoot data discrepancies and identify root causes.
Create and maintain dashboards and recurring reports using Power BI and Excel.
Translate business questions into metrics, KPIs, reports, and visualizations.
Ensure reporting is accurate, performant, and refreshed according to business requirements.
Use operational data to support business decisions involving staffing, room-cleaning requirements, food supply planning, and resource allocation.
Serve as a liaison between Product and Engineering teams by translating business requirements into technical specifications and communicating technical constraints to business stakeholders.
Gather requirements, prioritize requests, manage stakeholder expectations, and present findings to technical and non-technical audiences.