Senior Data Engineer – LATAM based

Arionkoder

. Build the structured core of a governed data foundation on Databricks .

Posted 10/31/2026contractRemoteSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building production-grade data pipelines and models using Databricks, SQL, and Python, while ensuring data governance and quality through effective testing and access control. Capable of collaborating with business stakeholders to clarify definitions and permissions, and utilizing AI tools for enhanced data management.

Highest-signal resume keywords

Databricks ExpertiseExpert SQLData ModelingData GovernanceAPI Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLData ModelingData Quality TestingIncremental ProcessingChange Data CaptureEntity ResolutionTemporal ValidityProvenanceLineage

Soft Skills

Autonomous WorkCollaborationClarifying DefinitionsPrioritizationOutcome Ownership

Tools & Technologies

DatabricksUnity CatalogAI Coding ToolsDbtGreat ExpectationsCI/CD

Industry Keywords

Data GovernanceAccess ControlMaster Data ManagementMulti-Tenant Data IsolationData ConsolidationUnstructured Content GovernanceFinOps

Tech Stack

Tools & technologies

PySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Build the structured core of a governed data foundation on Databricks
Reconcile business entities across systems with different identifiers
Preserve facts with their source and validity period
Turn business definitions into certified tables
Implement access control and application-level permission enforcement
Build APIs and MCP tools that serve data according to caller permissions
Work autonomously with business stakeholders and clarify definitions and permissions
Collaborate in a small team alongside the client’s data platform team
Follow client conventions and hand over completed work
Provide trusted data for AI agents, applications, and business teams
Use AI tools for modeling, SQL, testing, and documentation while validating their output

Requirements

What you’ll need

6+ years of professional data engineering, building production-grade pipelines and data models
3+ years hands-on with Databricks in production, including Unity Catalog
Expert SQL and Python; Spark/PySpark a plus
Strong data modeling, including SCD Type 2, effective dating, temporal validity, provenance, and lineage
Data quality and testing discipline, including dbt tests, Great Expectations, or similar, and CI/CD for data
Experience reconciling data across systems, including entity resolution or master data
Incremental and change-driven processing, including CDC, streaming, or incremental frameworks
Practical data governance and production access control, including row-level security, column masking, or role/attribute-based access
Experience building APIs or services that serve data
Ability to work autonomously, challenge unclear definitions, prioritize by risk, and own outcomes
Daily use of AI coding tools such as Claude, Cursor, or similar
C1 English; comfortable working fully remote and directly with a client team
Preferred: APIs or MCPs, multi-tenant data isolation, NetSuite or Salesforce, data consolidation across acquired companies or business units, unstructured content governance, semantic or metrics layers, FinOps/cost attribution

Benefits

Comp & perks

Monthly USD Service Fee
20 business days of paid Agreed Time Off—Annual + 6 Local Holidays
Caregiver Time Off
A dynamic remote work culture; you can work from anywhere
An entrepreneurial environment