1150 - Senior Data Platform Architect - Palantir Foundry & Databricks Integration

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OtherPlatform Architect

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Quick Summary

Key Responsibilities

Design and implement enterprise-scale federated architectures integrating Palantir Foundry and Databricks. Establish standards for data sharing across Foundry, Databricks, BigQuery,

Requirements Summary

8+ years of experience in Data Engineering, Data Architecture, or Platform Engineering. 8+ years of experience with Databricks Lakehouse Architecture.

Technical Tools

OtherPlatform Architect

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 Data Platform Architect - Palantir Foundry & Databricks Integration, 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 implement enterprise-scale federated architectures integrating Palantir Foundry and Databricks.
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Establish standards for data sharing across Foundry, Databricks, BigQuery, and Cloud Storage environments.
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Define architecture patterns leveraging Delta Lake, Apache Iceberg, Unity Catalog, Foundry Ontology, Virtual Tables, and Catalog Federation.
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Lead the modernization of legacy ETL architectures toward metadata-driven, cloud-native data products.
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Define enterprise data governance, lineage, metadata, and ownership models across both platforms.
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Create architectural roadmaps supporting AI, machine learning, real-time analytics, and self-service data consumption.
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Design and implement Foundry Databricks Connector solutions, including bulk imports, incremental data synchronization, virtual tables, compute pushdown, and external model integrations.
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Build scalable ingestion, transformation, and enrichment pipelines using PySpark, Spark SQL, Python, Databricks Workflows, Airflow, and Foundry Code Repositories.
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Architect secure connectivity between Palantir Foundry, Databricks, Google Cloud Platform, BigQuery, Cloud Storage, and Enterprise APIs.
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Enable AI and machine learning workloads across Foundry and Databricks environments.
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Serve as the technical authority for enterprise data platform architecture and lead architecture reviews.

Requirements

~1 min read

8+ years of experience in Data Engineering, Data Architecture, or Platform Engineering.
8+ years of experience with Databricks Lakehouse Architecture.
Experience implementing or operating Palantir Foundry data platforms.
Deep expertise in Databricks, PySpark, Spark SQL, Delta Lake, Python, and Data Modeling.
Strong knowledge of Unity Catalog, Apache Iceberg, Lakehouse Architectures, Data Governance, and Metadata Management.
Hands-on experience with Google Cloud Platform, including BigQuery, Cloud Storage, Pub/Sub, IAM, and Networking.
Experience designing highly scalable distributed data systems.
Strong architecture, leadership, and stakeholder management skills.

Nice to Have

~1 min read

Palantir Foundry certification or implementation experience.
Experience with Ontology development and operational decision platforms.
Experience with AI/ML infrastructure and model deployment.
Familiarity with Terraform, Kubernetes, GitHub Actions, and CI/CD Pipelines.
Experience with survey, consumer intelligence, marketing, or ad-tech data platforms.
Experience supporting data products at Fortune 500 scale.