1178 - Sr. Data Architect

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Data ArchitectData & AI

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Quick Summary

Key Responsibilities

Design and own the end-to-end lakehouse architecture on Databricks, using Medallion (bronze/silver/gold) patterns. Build and optimize scalable batch and streaming pipelines in PySpark,

Requirements Summary

10+ years in data engineering, including 5+ years hands-on with Databricks and Spark in production. Strong Python and PySpark; working knowledge of Scala and advanced SQL.

Technical Tools

Data ArchitectData & AI

Hello! We are GoFasti, a Talent-as-a-Service. GoFasti bridges the gap between world-class developers and designers from LatAm and first-class companies around the globe.

We need an English-fluent Senior Sr. Data Architect, based in Latin America, available to work remotely.

We are looking for someone with exceptional communication and relationship-building skills, who embraces changes while maintaining strong attention to detail. An interested and proactive person, who's constantly learning and improving their skills.

Are you the one we are looking for?

Responsibilities

~1 min read

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Design and own the end-to-end lakehouse architecture on Databricks, using Medallion (bronze/silver/gold) patterns.
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Build and optimize scalable batch and streaming pipelines in PySpark, Spark SQL and Python.
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Lead platform migrations (e.g., legacy data warehouse or Hadoop/EMR to Databricks) with measurable gains in cost and run time.
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Define data governance: Unity Catalog, fine-grained access control, auditing, lineage and compliance (GDPR and similar).
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Model data for analytics and operations (OLTP/OLAP, dimensional, SQL and NoSQL).
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Set engineering standards: CI/CD, unit and integration tests, code review, reusable Python packages, Databricks Asset Bundles.
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Manage infrastructure as code with Terraform and drive FinOps practices to control cloud spend.
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Evaluate and prototype AI use cases on the platform (LLMs, vector databases, agents, MLflow).
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Advise other teams on architecture and mentor junior and mid-level engineers.

Requirements

~1 min read

10+ years in data engineering, including 5+ years hands-on with Databricks and Spark in production.
Strong Python and PySpark; working knowledge of Scala and advanced SQL.
Proven record designing data lakes, data warehouses and lakehouses, including at least one large migration you led.
Production experience on at least one major cloud (AWS, Azure or GCP).
Hands-on data governance with Unity Catalog, access controls, lineage and auditing.
Solid software engineering practice: Git workflows, automated testing, CI/CD (Azure DevOps, GitHub Actions or similar).
Infrastructure as code with Terraform.
Ability to explain design trade-offs clearly to engineers and non-technical stakeholders.
Experience mentoring engineers.
English at C1 level or higher.

Nice to Have

~1 min read

Databricks certifications (e.g., Platform Administrator, Data Engineer Professional).
AWS Solutions Architect or equivalent cloud architecture certification.
Multi-cloud experience across AWS, Azure and GCP.
Experience building agentic or RAG solutions with LangChain, LangGraph, MLflow, OpenAI APIs and vector databases.
Real-time and IoT data processing at high volume.
Background in finance, telecom, payments or SaaS data domains.
Spanish or Portuguese.

What We Offer

~1 min read

✓The salary range offered for this position varies from (USD) $7,000 - $8,800 per month, depending on seniority and skillset.

✓This position is for a full time contract, through a payroll platform.

✓The talent will work remotely allocated at our client.

Location & Eligibility

Where is the job

Worldwide

Fully remote, anywhere in the world

Who can apply

Same as job location

About this job

Pay per year: ≈ $84,000–$105,600 a year; 41% below the $161,447 median for Data Architect jobs on Jobera (38 salaries).
Posted: Today
Employer: has 19 open jobs on Jobera.