16 days ago
Campinas, BrazilSenior
Responsibilities
- Own the technical design and delivery of data models for a BEES business domain.
- Profile source systems and Unity Catalog tables to assess grain, keys, cardinality, overlap, nulls, and derivations.
- Create and evolve canonical logical models, canonical datasets, mappings, transformations, lineage, and documented semantics.
- Design master-data outcomes including entity resolution, blocking keys, duplicate handling, cross-system identity, and survivorship rules.
- Define data-quality expectations and contribute to data-quality framework and tooling for executable checks and monitoring.
- Shape models for data scientists, data analysts, curated tables, metric views, and feature tables.
- Contribute Python packages, SQL and Spark code on Databricks, YAML definition contracts, entity classification, lineage-aware mappings, and tests.
- Drive entity and attribute lifecycle changes, including creation, renaming, deprecation, and retirement.
- Review model, mapping, and ontology-aligned dataset changes and escalate cross-domain ownership conflicts.
- Mentor engineers through design reviews, source-analysis pairing, hands-on support, and documentation.
Requirements
- Senior experience as a data engineer, data analyst, or equivalent data-focused professional designing conceptual and logical models from operational source systems in complex businesses.
- Demonstrated ability to turn ambiguous business context and imperfect data into models with explicit entities, grain, keys, relationships, and cardinalities.
- Hands-on master-data management experience with deterministic and probabilistic matching, blocking, duplicate detection, golden-record or survivorship rules, and cross-system identity.
- Experience designing and applying data-quality checks for uniqueness, referential integrity, validity, completeness, consistency, reconciliation, and timeliness.
- Production SQL experience with joins, aggregations, and window functions; batch ELT experience; and sufficient PySpark or Spark SQL experience to profile sources and prototype conformed datasets on Databricks.
- Ability to contribute to a Python codebase by modifying packages, adding tests, and taking pull requests through review.
- Experience with catalog or metadata systems, physical table and column mappings, lineage, and data contracts.
- Experience reviewing other engineers' models and code and mentoring through design feedback and documentation.
- Experience collaborating in GitHub or Azure DevOps, including reviewing changes from outside the immediate team.
- Clear written and verbal communication with business stakeholders, data scientists, and data analysts.
- Bachelor's degree in computer science, engineering, information systems, or another quantitative field, or equivalent practical experience.
- Preferred experience in data management and governance, business glossaries, critical data elements, stewardship, naming standards, dataset certification, Azure Databricks, Unity Catalog, feature or metric grain, slowly changing attributes, point-in-time correctness, entity classification, schema matching, duplication discovery, or marketplace, B2B, or B2C businesses.
Benefits
- Performance-based bonus, attendance bonus, private pension plan, meal allowance, days off, and health, dental, and life insurance plans, subject to applicable rules.
- Casual office and dress code.
- Discounts on medications and AB InBev products, WellHub partnership, Clube Ben partnership, childcare assistance, scholarship program, school supplies support, language learning platforms and training, and transportation allowance.
Tech Stack
Categories
Data Engineering
About BEES
BEES builds a B2B digital commerce and marketplace platform for small and medium retailers to order products, manage invoices, and track deliveries from AB InBev and partner suppliers. The business supports online ordering, promotions, and data-driven sales tools across 29 countries. Created by and owned by AB InBev, BEES is headquartered in Rotkreuz, Zug, and focuses on digitizing distributor-to-retailer workflows in beverage and adjacent categories.