Lead Data Platform Engineer (Palantir or Databricks)

Job Description Roles & Responsibilities Project description Role 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 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. 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 or Databricks. 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 Palantir or Databricks platforms. 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: C1 Advanced Seniority Senior Desired Candidate Profile 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 or Databricks. 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 Palantir or Databricks platforms. 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: C1 Advanced Company Industry IT - Software Services Department / Functional Area IT Software Keywords Lead Data Platform Engineer (Palantir Or Databricks) Get real-time job updates only on our App