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# 1150 – Senior Data Platform Architect – Palantir Foundry & Databricks Integration

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/gofasti.md)ShareRemote from[LATAM](https://jobicy.com/job-region/latam.md)SalaryUSD 6k–7k / moDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentContractExperienceSeniorPublished6 Oct 2026Apply before5 Nov 2026Listing views56Application actions5Application toolkit

## Make your next move.

Prepare your resume, explore your fit, and draft a cover letter for this opportunity.

AI Summary

## The role, at a glance.

This senior data architecture contract role leads the design of federated enterprise data platforms spanning Palantir Foundry, Databricks, Google Cloud Platform, BigQuery, and Cloud Storage. The architect will define governance, lineage, metadata, data-sharing, and ownership standards while modernizing legacy ETL into cloud-native, metadata-driven data products. Core hands-on responsibilities include implementing Foundry–Databricks connector patterns, scalable Spark pipelines, secure integrations, and AI/ML-enabled analytics workloads. The position requires deep Databricks Lakehouse expertise, Palantir Foundry experience, strong GCP knowledge, and the ability to act as a technical authority with senior stakeholders. It is a remote full-time contract opportunity restricted to candidates based in Latin America.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

4/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a highly specialized architecture role requiring 8+ years of experience and rare combined expertise in Palantir Foundry, Databricks, distributed data platforms, governance, and GCP. The architect is expected to set enterprise standards, lead reviews, and make cross-platform technical decisions with substantial business impact.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianBelow market$6,500US market range$160k–$230k0$253k

AI insightThe disclosed contract compensation is USD 6,000-7,000 per month, with a midpoint of USD 6,500 per month (approximately USD 78,000 annually if paid for 12 months). For the US market, a senior enterprise data platform architect with Databricks, GCP, and Palantir Foundry expertise would commonly command an estimated annual base-pay market range of USD 160,000-230,000; this market estimate is annualized and may differ materially from a LATAM remote contractor rate.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Palantir Foundry](https://jobicy.com/jobs?search_keywords=Palantir%20Foundry.md)[Databricks](https://jobicy.com/jobs?search_keywords=Databricks.md)[Data Platform Architecture](https://jobicy.com/jobs?search_keywords=Data%20Platform%20Architecture.md)[Data Engineering](https://jobicy.com/jobs?search_keywords=Data%20Engineering.md)[PySpark](https://jobicy.com/jobs?search_keywords=PySpark.md)[Spark SQL](https://jobicy.com/jobs?search_keywords=Spark%20SQL.md)[Delta Lake](https://jobicy.com/jobs?search_keywords=Delta%20Lake.md)[Apache Iceberg](https://jobicy.com/jobs?search_keywords=Apache%20Iceberg.md)[Google Cloud Platform](https://jobicy.com/jobs?search_keywords=Google%20Cloud%20Platform.md)[Data Governance](https://jobicy.com/jobs?search_keywords=Data%20Governance.md)

Sample interview questionsHow would you design a federated architecture between Palantir Foundry and Databricks while avoiding unnecessary data duplication?I would first classify data products by ownership, latency, governance requirements, and compute location. I would use catalog federation, virtual tables, and Foundry–Databricks connector capabilities where appropriate, reserving physical replication for performance, resiliency, or operational requirements. I would also establish shared metadata, lineage, access-control, and data-contract standards so consumers can discover and trust products regardless of platform.

What is your approach to migrating a legacy ETL estate to metadata-driven cloud-native data products?

I begin with an inventory of pipelines, source dependencies, SLAs, data quality issues, and business-critical outputs. I then prioritize migrations by risk and value, define reusable ingestion and transformation patterns, and introduce metadata-driven orchestration, testing, observability, lineage, and versioned data contracts. The migration should proceed incrementally with parallel validation and measurable reliability and cost outcomes.

How would you establish governance across Databricks, Foundry, BigQuery, and Cloud Storage?

I would define a common governance operating model covering ownership, classification, access requests, retention, quality expectations, and auditability. Unity Catalog, Foundry governance capabilities, GCP IAM, and BigQuery permissions would be aligned to consistent role- and attribute-based access patterns. Central metadata and lineage standards would provide a cross-platform view, while automated policy checks would reduce manual governance overhead.

Describe how you would optimize a large-scale PySpark pipeline that is missing its processing SLA.

I would use Spark UI and workload metrics to identify whether the primary constraint is data skew, excessive shuffling, poor partitioning, inefficient joins, file sizes, or cluster configuration. Typical improvements include applying predicate and column pruning, repartitioning appropriately, using broadcast joins selectively, compacting small files, leveraging Delta optimization features, and tuning autoscaling and executor resources. I would validate each change with representative workloads and track runtime, cost, data quality, and reliability.

How do you communicate complex architecture tradeoffs to executive and nontechnical stakeholders?

I frame the decision around business outcomes such as delivery speed, risk reduction, compliance, reliability, and cost rather than product features alone. I present a concise set of viable options, make assumptions explicit, quantify implications where possible, and recommend a path with clear milestones and ownership. For technical teams, I supplement this with detailed architecture diagrams, standards, and implementation guidance.

Opportunity details

## About this role.

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.

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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.

*

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.

*

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.

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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:

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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.

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Deep expertise in Databricks, PySpark, Spark SQL, Delta Lake, Python, and Data Modeling.

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Strong knowledge of Unity Catalog, Apache Iceberg, Lakehouse Architectures, Data Governance, and Metadata Management.

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Hands-on experience with Google Cloud Platform, including BigQuery, Cloud Storage, Pub/Sub, IAM, and Networking.

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Experience designing highly scalable distributed data systems.

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Strong architecture, leadership, and stakeholder management skills.

It’s a plus:

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Palantir Foundry certification or implementation experience.

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Experience with Ontology development and operational decision platforms.

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Experience with AI/ML infrastructure and model deployment.

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Familiarity with Terraform, Kubernetes, GitHub Actions, and CI/CD Pipelines.

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Experience with survey, consumer intelligence, marketing, or ad-tech data platforms.

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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!

Show more

[Apply now >](https://jobicy.com/jobs/154742-1150-senior-data-platform-architect-palantir-foundry-databricks-integration.md)

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