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BEES

Runs a digital ordering platform for small retailers

Intermediate Data Operations Analyst

Data ManagementConfirmed live in the last 24 hours
Full-timeCampinas - State of São Paulo, BrazilIn-person

About the Job

Requirements

  • Bachelor's degree in Computer Science, Data Science, Information Technology, Engineering, or a related field.
  • Proven experience in Data Operations, Data Analysis, Support Engineering, or a similar hybrid role.
  • Strong SQL skills, with Snowflake preferred, and ability to query and analyze large datasets.
  • Experience with PySpark or Scala in Databricks environments.
  • Familiarity with NoSQL databases, including MongoDB and Cosmos DB.
  • Understanding of data pipeline concepts and architectures, including ETL/ELT and Bronze/Silver/Gold data lake layers.
  • Experience with data quality dimensions: accuracy, completeness, validity, consistency, timeliness, and uniqueness.
  • Familiarity with Git and git-flow practices.
  • Intermediate knowledge of analytics infrastructure, including Databricks/Unity Catalog, Data Factory, Power BI, and Azure Storage/Data Lake.
  • Experience with ITIL-aligned incident management processes and SLA-driven environments.
  • Ability to read and interpret data flow diagrams, API contracts/Swagger, and system architectures.
  • Advanced English, written and verbal.
  • Ability to investigate root causes and connect findings across systems.
  • Ability to communicate technical findings clearly to stakeholders at all levels.
  • Ability to anticipate and respond to problems before they escalate.
  • Ability to document work and support knowledge reuse and operational consistency.
  • Ability to work collaboratively across Engineering, Product, and Analytics teams.
  • Ability to manage multiple incidents under pressure and prioritize effectively.
  • Self-motivation, curiosity, and desire to continuously learn and improve operational maturity.
  • Ability to work in a global, multi-country support context.

Responsibilities

  • Perform triage, initial diagnosis, and impact analysis of data incidents, classifying incidents by severity, urgency, and business impact.
  • Conduct first-level data analysis using data consistency and data quality checklists, and second-level analysis to source data issues for onboarded data products.
  • Identify the type and location of issues in data production, processing, or consumption by validating the full workflow and pipeline.
  • Respond to bug reports in compliance with SLAs, including deadlines, severity, escalation paths, and notifications.
  • Participate in Sev1/Sev2 War Rooms and crisis responses as L2 support.
  • Troubleshoot using SQL, PySpark/Scala in Databricks, and NoSQL databases including MongoDB.
  • Perform complex ad-hoc data extractions for audits, one-off analyses, and incident investigations.
  • Validate data flows end-to-end from source systems such as CosmosDB, through Bronze/Silver/Gold processing layers, to consumption via dashboards, APIs, and data sharing.
  • Execute configuration updates to pipeline parameters, reference tables, and business rules.
  • Perform technical interventions in production SQL and NoSQL databases to correct application states when required.
  • Develop action plans based on root cause analysis and connect cross-team investigative processes.
  • Identify patterns in recurring issues and propose improvements or optimizations to Engineering and Product teams.
  • Contribute to proactive incident detection by monitoring instrumented alerts, including job health checks and data consistency alerts.
  • Identify, communicate, and manage operational risks before they escalate.
  • Proactively communicate the status of each open ticket to impacted stakeholders.
  • Facilitate communication between Operational and Analytical teams, bridging Data Engineering, Data Analytics, and Product/Application teams.
  • Engage technical specialists and escalate to the Incident Specialist when applicable.
  • Follow up with project teams to ensure resolution deadlines and customer satisfaction.
  • Connect with Data Product Managers to stay updated on KPIs, report catalogs, and domain data entity catalogs.
  • Create, maintain, and continuously improve a structured knowledge base, including runbooks, troubleshooting guides, and resolution records.
  • Document evidence, resolution steps, and root causes for every incident.
  • Contribute to data flow diagrams and operational documentation using collaborative tools such as Lucidchart and Confluence.
  • Maintain understanding of product data flows and platform architecture to support effective diagnosis.
  • Execute planned data operations and standard service requests, including data extractions and configuration updates.
  • Define and refine data-related SLAs with stakeholders, including flows, severities, and MTR.
  • Provide follow-up on metrics related to ticket resolution, SLA compliance, and product impact.

Desired Qualifications

  • Snowflake experience.
  • Knowledge of dbt, including SQL and Jinja.
  • Basic understanding of DevOps Engineering, including Azure Pipelines and Terraform.
  • Experience with telemetry and observability tools, including Segment, Mixpanel, and OpsGenie.
  • Familiarity with Azure Cost Analysis.
  • Experience with data governance tools, including Atlan and Unity Catalog.
  • Knowledge of data sharing protocols, including Azure Delta Sharing and Standard Data Offerings.

About the Company

BEES

Runs a digital ordering platform for small retailers

BEES runs a business-to-business commerce platform where small and medium-sized retailers order stock from brewer AB InBev and other consumer brands. AB InBev created it to digitize how its brands reach retailers, and other brand owners and distributors use the same system to run their own sales and delivery. Its connected tools cover ordering, payments, delivery management, customer service and data for management teams. Built-in AI recommends products and offers to each retailer and plans sales visits and delivery routes for field teams. BEES first ran in the Dominican Republic before expanding to other countries, and it is headquartered in Rotkreuz, Switzerland.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Risch-Rotkreuz, Switzerland
Founded
2019

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