Senior Data Platform Architect

Luxoft

Location not specified Remote

Posted: December 5, 2025

Required Skills

Job Description

Project description

We are seeking an expert with deep proficiency as a Platform Engineer, possessing experience in data engineering. This individual should have a comprehensive understanding of both data platforms and software engineering, enabling them to integrate the platform effectively within an IT ecosystem.

Responsibilities

Manage and optimize data platforms (Databricks, Palantir).

Ensure high availability, security, and performance of data systems.

Provide valuable insights about data platform 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.

Skills

Must have

Minimum 10 Years of experience in IT/Data.

Minimum 5 years of experience as a Data Platform Engineer/Data Engineer.

Bachelor's in IT or related field.

Infrastructure & Cloud: Azure, AWS (expertise in storage, networking, compute).

Data Platform Tools: Any of Palantir, Databricks, Snowflake.

Programming: Proficiency in PySpark for distributed computing and Python for ETL development.

SQL: Expertise in writing and optimizing SQL queries, preferably with experience in databases such as PostgreSQL, MySQL, Oracle, or Snowflake.

Data Warehousing: Experience working with data warehousing concepts and platforms, ideally Databricks.

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).

Other

Languages

English: B2 Upper Intermediate

Seniority

Lead

Remote Spain, Spain

Req. VR-112304

DWH Development

BCM Industry

04/12/2025

Req. VR-112304

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