Top Data Analyst Jobs in Brasilia

Analyze customer behavior and product performance using large datasets; build dashboards, reports, and visualizations; develop queries and data models; perform statistical analysis, forecasting, segmentation, and A/B testing; collaborate with cross-functional teams and present actionable insights to stakeholders while improving data quality and analytics processes.

The Data Analyst will design interactive dashboards, model data, perform ETL processes, and collaborate with teams to enhance data-driven decisions using Power BI.

Lead analytics engagements for enterprise clients using observability and digital experience data. Manage 4–8 accounts, deliver dashboards and reports, perform ad-hoc analysis, configure Dynatrace solutions, present findings to technical and executive stakeholders, and influence product roadmap and client performance strategies.

Develop analytics solutions, collaborate on requirements, manage data quality, and create visualizations while improving reporting and platforms.

Design and maintain Power BI dashboards, build data models and DAX measures, extract/transform data with SQL and Excel, automate reports, perform data quality analysis, and present insights to finance and business stakeholders.

Build and maintain analytics data models, dashboards, and reports. Use SQL (Postgres, Trino, Iceberg) and dbt to power financial metrics. Perform deep-dive analyses using SQL and Python (Jupyter, Pandas) to answer business questions, operationalize data, and improve reporting and automation.

Perform exploratory data analysis, build and maintain Power BI dashboards, ensure data quality through cleansing and validation, collaborate with cross-functional teams to deliver data-driven insights, document methodologies and data assets, and present findings to business stakeholders.

Lead data analytics work: collect, clean, model, analyze, and visualize large datasets; build dashboards and reports (SnowSight, Power BI); design data models and implement Snowflake/dbt pipelines; ensure data governance and quality; mentor junior analysts and partner with cross-functional teams to deliver insights.

Build and maintain Power BI dashboards and KPIs, perform advanced SQL analyses, monitor data quality, collaborate with product and data engineering, support metric standardization and CI/CD for BI, and deliver ad hoc analyses to inform business decisions.

Work with real-world datasets to clean, transform, and analyze data using Python and spreadsheets; perform exploratory analysis, develop data models, support client reporting, and communicate insights to cross-functional teams to drive e-commerce decisions.

The role involves creating analytical workflows, maintaining data integrity, and translating business requirements into data solutions with Power BI and other tools.

Analyze billing and support performance, build and maintain data pipelines, apply statistical forecasting and A/B testing, collaborate cross-functionally, document analyses, and provide recommendations to reduce financial risk, disputes, churn, and operational inefficiencies.

The Senior Associate Decision Scientist role involves providing analytics support by building reports and dashboards, writing SQL, and maintaining data models while collaborating with stakeholders to derive insights.

The role involves improving data pipelines, migrating legacy systems, and ensuring data accuracy, while utilizing strong SQL and Python skills for ETL/ELT processes.

The Lead Data Analyst will document technical systems, collaborate with engineering teams, manage SME availability, and produce clear, structured documentation.

Provide data analysis and reporting as a virtual assistant: create and maintain reports, perform data entry and validation, generate visual insights, collaborate with stakeholders, track action items, and improve workflows to optimize reporting efficiency.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

As a Data Analyst, you will deliver data solutions, optimize data pipelines, and provide actionable insights while collaborating closely with team members and stakeholders.

The Revenue Operations Data Analyst will analyze datasets, optimize dashboards, and develop data pipelines to support revenue operations and strategic decision-making.

Develop, optimize, and maintain SQL queries; refactor legacy reporting into a modern data warehouse; collaborate with Product and Development; provide technical support and troubleshooting; pair-program and produce technical documentation.

Collect, prepare, validate, and report statistical data for property and casualty insurance. Develop and maintain reports and analytic tools, support metadata and data dictionary upkeep, and coordinate with actuaries, product managers, regulatory affairs, finance, and IT to meet reporting requirements.

Build scalable analytical solutions and dashboards using Power BI, Databricks, SQL and Python. Design KPI frameworks, perform statistical analysis and experimentation, ensure data quality and governance, partner with Product/Commercial/Tech teams, and communicate insights to stakeholders.

Manage data migrations and reporting for new hotel clients: extract, clean, map, validate CSV/Excel data, troubleshoot formatting issues, run post-migration audits, and coach clients on building and automating operational and financial reports to track KPIs.

The role involves developing predictive analytics models using Python, creating reports, conducting data evaluation, and communicating insights to support business decisions.

Monitor and report on robotic and scanner fleets, answer customer calls and perform first-line troubleshooting, run queries to detect anomalies, escalate issues, and support new deployments with clear English documentation.