Senior Data Platform Architect, Palantir Foundry & Databricks Integration
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What you'll do
- Design and implement enterprise-scale federated architectures integrating Palantir Foundry and Databricks.
- Establish standards for data sharing across Foundry, Databricks, BigQuery, and Cloud Storage environments.
- Define architecture patterns leveraging Delta Lake, Apache Iceberg, Unity Catalog, Foundry Ontology, Virtual Tables, and Catalog Federation.
- Lead the modernization of legacy ETL architectures toward metadata-driven, cloud-native data products.
- Define enterprise data governance, lineage, metadata, and ownership models across both platforms.
- Create architectural roadmaps supporting AI, machine learning, real-time analytics, and self-service data consumption.
- Design and implement Foundry Databricks Connector solutions, including bulk imports, incremental data synchronization, virtual tables, compute pushdown, and external model integrations.
- Build scalable ingestion, transformation, and enrichment pipelines using PySpark, Spark SQL, Python, Databricks Workflows, Airflow, and Foundry Code Repositories.
- Architect secure connectivity between Palantir Foundry, Databricks, Google Cloud Platform, BigQuery, Cloud Storage, and Enterprise APIs.
- Enable AI and machine learning workloads across Foundry and Databricks environments.
- Serve as the technical authority for enterprise data platform architecture and lead architecture reviews.
What they're looking for
- 10+ years of experience in Data Engineering, Data Architecture, or Platform Engineering.
- 5+ 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
- 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.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
We Make Remote Work Remarkable • TopTalent from LatAm
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:
Design and implement enterprise-scale federated architectures integrating Palantir Foundry and Databricks.
Establish standards for data sharing across Foundry, Databricks, BigQuery, and Cloud Storage environments.
Define architecture patterns leveraging Delta Lake, Apache Iceberg, Unity Catalog, Foundry Ontology, Virtual Tables, and Catalog Federation.
Lead the modernization of legacy ETL architectures toward metadata-driven, cloud-native data products.
Define enterprise data governance, lineage, metadata, and ownership models across both platforms.
Create architectural roadmaps supporting AI, machine learning, real-time analytics, and self-service data consumption.
Design and implement Foundry Databricks Connector solutions, including bulk imports, incremental data synchronization, virtual tables, compute pushdown, and external model integrations.
Build scalable ingestion, transformation, and enrichment pipelines using PySpark, Spark SQL, Python, Databricks Workflows, Airflow, and Foundry Code Repositories.
Architect secure connectivity between Palantir Foundry, Databricks, Google Cloud Platform, BigQuery, Cloud Storage, and Enterprise APIs.
Enable AI and machine learning workloads across Foundry and Databricks environments.
Serve as the technical authority for enterprise data platform architecture and lead architecture reviews.
Requirements:
10+ years of experience in Data Engineering, Data Architecture, or Platform Engineering.
5+ 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.
It's a plus:
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.
Compensation:
The salary range offered for this position varies from (USD) $6,000 - $7,000 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.
Here are the steps for this process:
TBD > Application review/approval > Screening interview with GoFasti's team > We build and send your profile to our client > Profile review/approval by client > Interview with the client > Hiring and onboarding.
Once you apply for the job, our team will review your resume. If it meets the requirements, we will contact you and move forward in the process.
Note for Candidates Approached Directly:
If you were contacted directly by a member of our team and are interested in this opportunity, please do not apply through this link. Instead, reach out to the person who contacted you to coordinate a meeting.
Thank you!
Company
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