Lead Data Platform Engineer (Palantir or Databricks)

• Manage and optimize the Palantir data platform.
• Ensure high availability, security, and performance of data systems.
• Provide insights into data platforms usage.
• Design and maintain system libraries used in ETL pipelines.
• Optimize ETL processes for better performance., Palantir Foundry SQL Databases (PostgreSQL, MySQL, Oracle, Snowflake) ETL Tools Monitoring tools (Prometheus, Grafana) Docker Kubernetes Terraform Descripción del empleo Project description

Role Description - We are seeking an expert with deep proficiency as a Palantir Platform Engineer, possessing experience in data engineering and designing, building, and operationalizing AI-powered workflows, agents, and applications that drive tangible business outcomes. The ideal candidate is a self-starter, able to translate complex business needs into scalable technical solutions, and confident working directly with stakeholders to maximize the value of Foundry and AIP. Responsibilities

• Manage and optimize Palantir data platform.
• Ensure high availability, security, and performance of data systems.
• Provide valuable insights about data platforms usage.
• Optimize computing and storage for large-scale data processing.
• Design and maintain system libraries (Python) used in ETL pipelines and platform governance.
• Optimize ETL Processes - Enhance and tune existing ETL processes for better performance, scalability, and reliability.

AIP & AI Enablement

• Support the design and deployment of AIP use cases such as copilots, retrieval workflows, and decision-support agents.
• Ground agents and logic flows using RAG (retrieval-augmented generation) by connecting to relevant data sources, embedding/vector search, ontology content.
• Use Ontology-Augmented Generation (OAG) when needed: operational decision-making where logic, data, actions and relationships are embedded in the Ontology.
• Collaborate with senior engineers on agent design, instructions, and evaluation using AIP's native features.

Luxoft Spain is seeking a Palantir Platform Engineer in O Chazo, Galicia. This role involves managing the Palantir data platform and optimizing it for performance and availability. The ideal candidate will leverage their extensive experience in data engineering and operationalizing AI-driven workflows to drive business outcomes.

With a strong understanding of AIP features, Python, and SQL, the candidate will design scalable solutions and collaborate directly with stakeholders. This position requires a Bachelor's degree and at least 10 years in IT, with significant experience in Palantir Foundry., * At least 10 years of experience in IT or Data.

• 5 years of experience as a Data Platform Engineer or Data Engineer.
• 3 years of experience with Palantir Foundry.
• Practical experience with AIP workflows.
• Bachelor's in IT or related field., 10+ years of experience in IT/Data 5+ years as Data Platform Engineer/Data Engineer 3+ years with Palantir Foundry Experience supporting AIP features like RAG workflows Bachelor's in IT or related field Cloud expertise (Azure, AWS) Proficiency in PySpark Proficiency in Python for ETL SQL expertise Familiarity with ETL tools Experience with data modelling Proficiency with Git Familiarity with monitoring tools Experience with data quality tools

Educación

Bachelor's in IT or related field, Must have

• Minimum 10 Years of experience in IT/Data.
• Minimum 5 years of experience as a Data Platform Engineer/Data Engineer.
• Minimum 3 years of experience with Palantir Foundry.
• Practical experience using or supporting AIP features such as RAG workflows, copilots, or agent-based applications.
• Bachelor's in IT or related field.
• Infrastructure & Cloud: Azure, AWS (expertise in storage, networking, compute).
• Proficiency in PySpark for distributed computing.
• Proficiency in Python for ETL development.
• SQL: Expertise in writing and optimizing SQL queries, preferably with experience in databases such as PostgreSQL, MySQL, Oracle, or Snowflake.
• ETL Tools: Familiarity with ETL tools & processes.
• Data Modelling: Experience with dimensional modelling, normalization/denormalization, and schema design.
• Version Control: Proficiency with version control tools like Git to manage codebases and collaborate on development.
• Data Pipeline Monitoring: Familiarity with monitoring tools (e.g., Prometheus, Grafana, or custom monitoring scripts) to track pipeline performance.
• Data Quality Tools: Experience implementing data validation, cleaning, and quality frameworks, ideally Monte Carlo.

Nice to have

• Containerization & Orchestration: Docker, Kubernetes.
• Infrastructure as Code (IaC): Terraform.
• Understanding of Investment Data domain (desired).