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. 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). Benefits Flexible work schedule Great company culture and friendly environment Work within a fast-moving, exciting, and challenging environment Talent development ecosystem Luxoft Training Center services with ad-hoc leadership and technical programs Knowledge sharing in professional communities Meetings for knowledge sharing, celebrations, and brainstorming : your ideas count! Regular team-building activities Variety of discounts for our employees J-18808-Ljbffr