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Data Engineering Manager (Databricks)

RemoteChile only
Published
Role
Data Engineering
Experience
Senior
Employment
Full-time
Salary not disclosed
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Open to CL only. Set where you work from to check your eligibility.

No BS summary

Senior Data Engineering manager for Databricks-driven semantic layers and KPI/metric modelling. Must have 7+ years in data engineering, strong SQL and Python, experience with Databricks Metric Views/Azure Databricks and Medallion-style architectures. Based in Santiago, Chile (LATAM) with flexible/hybrid work options.

Core skills

Databricks Metric ViewsSQLKPI/metric modeling

Required skills

DatabricksAzure DatabricksPythonELT/ETL toolingGitData modelingConformed dimensionsMedallion architectureData profilingData qualityData lineageSemantic modelingFeature preparation for LLMs

Optional skills

FMCG/CPGPOSSKU and category dataSnowflakeAWS

Required languages

English Advanced (required)

What you'll do

  • Design, build, and maintain semantic layers and KPI models using Databricks Metric Views to underpin governed executive scorecards and AI-powered analytical solutions.
  • Work directly with business owners to define, validate, and translate KPI requirements into reusable data models and business logic.
  • Profile source data quality, ownership, data grain, and reconciliation requirements across enterprise source systems.
  • Design and implement data integration and transformation pipelines that prepare enterprise data for AI-generated narratives and conversational analytics.
  • Define conformed dimensions and market-specific data variations to support multi-market reporting and analytics.
  • Collaborate closely with Business Analysts and AI Engineers to align KPI definitions with underlying data structures and business ontologies.
  • Establish and enforce data quality, validation, and monitoring frameworks across all data assets feeding analytical applications.
  • Implement security, access control, and governance practices aligned with platform and AI governance standards.
  • Lead technical documentation and knowledge transfer initiatives at the conclusion of each delivery phase.
  • Support production readiness assessments and oversee the deployment of solutions to production environments.

What they require

  • 7+ years of experience in Data Engineering, with demonstrated expertise in semantic layer and KPI/metric modeling.
  • Strong hands-on experience building and maintaining Databricks Metric Views or equivalent semantic/metric layer tooling.
  • Advanced proficiency in SQL and Python for data processing, transformation, and pipeline development.
  • Solid understanding of cloud data platforms, specifically Azure Databricks, and modern ELT/ETL tooling.
  • Demonstrated expertise in data modeling techniques, conformed dimensions, and Medallion-style architectures.
  • Experience profiling data quality, lineage, and reconciliation across multiple source systems.
  • Comfort working directly with business stakeholders to gather, validate, and implement KPI requirements.
  • Understanding of business ontology and semantic modeling concepts.
  • Proficiency with Git version control and collaborative development practices.
  • Knowledge of how data engineering supports AI/LLM-based analytics, including feature preparation for narrative generation and conversational analytics.
  • Experience with FMCG/CPG or retail data ecosystems (POS, SKU, category, and market performance datasets) is a plus.
  • English: Advanced (required for effective communication with global teams)
  • 7+ years of experience in Data Engineering or related disciplines such as Data Architecture or Analytics Engineering, with demonstrated expertise in semantic modeling, KPI development, and multi-source data integration.

Benefits

  • Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
  • Access to AI learning paths to stay up to date with the latest technologies.
  • Study plans, courses, and additional certifications tailored to your role.
  • Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
  • English lessons to support your professional communication.
  • Travel opportunities to attend industry conferences and meet clients.
  • Career development plans and mentorship programs.
  • Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
  • Company-provided equipment.
  • Flexible working options; other benefits may vary according to your location in LATAM.

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What people say about this company

3.8/ 5

Salary not disclosed