Palantir Data engineer

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Experience: 5+ yrs

Location: Bengaluru, Hyderabad, Telangana

Job Type: Full-time

We are looking for an experienced Senior Data Engineer with strong expertise in Python, PySpark, SQL, and Palantir Foundry to design and implement scalable data analytics solutions on enterprise data platforms.

The role requires strong hands-on experience in distributed data processing, data modelling, data transformation, and analytical solution design. You will work closely with business and technical stakeholders to understand complex requirements and translate them into scalable, maintainable, and best-fit data architectures.

The ideal candidate will be comfortable working with large-scale software systems and enterprise data environments while contributing to end-to-end data engineering and analytics initiatives.

Requirements

Key Responsibilities

• Design, develop, and implement scalable data analytics and engineering solutions using Palantir Foundry.
• Build robust data pipelines and transformation workflows using PySpark, Python, and SQL.
• Work extensively with the Palantir Foundry platform to develop and manage enterprise data solutions.
• Translate customer and business requirements into scalable technical designs and data architectures.
• Design and implement end-to-end data management solutions for analytical use cases.
• Develop effective data models, transformation logic, datasets, and analytical workflows.
• Process and transform large datasets using distributed computing technologies such as Spark, Hive, and Hadoop.
• Develop efficient SQL queries, with strong preference for Spark SQL experience.
• Collaborate with architects, data scientists, analysts, engineers, and business stakeholders throughout the solution lifecycle.
• Analyse existing data structures and identify opportunities to improve data quality, performance, and usability.
• Participate in solution architecture, technical design, development, testing, deployment, and production support.
• Ensure data solutions are scalable, maintainable, reliable, and aligned with enterprise standards.
• Work within Agile/Scrum development environments and contribute to sprint planning, reviews, and technical discussions.
• Contribute to technical documentation, data architecture specifications, and implementation guidelines.
• Leverage cloud technologies such as AWS or Azure where applicable.
• Collaborate effectively with globally distributed and multicultural teams.
• Identify opportunities to improve data engineering processes, solution performance, and development efficiency.

What Makes You a Great Fit

• 5+ years of hands-on experience in data engineering, data analytics, or large-scale software development.
• Strong proficiency in Python, PySpark, and SQL, with practical experience building production-grade data solutions.
• Mandatory hands-on experience with Palantir Foundry.
• Strong experience designing and implementing data analytics solutions on enterprise data platforms.
• Proven experience with data modelling, data transformation, data management, and analytical use cases.
• Strong understanding of distributed computing technologies such as Apache Spark, Hive, or Hadoop.
• Strong SQL expertise, preferably including Spark SQL.
• Experience translating complex customer requirements into effective technical designs and architectures.
• Experience working with large-scale software systems and enterprise data environments.
• Exposure to AWS or Azure cloud environments is an advantage.
• Familiarity with JavaScript, HTML, and CSS is a plus.
• Experience working in Agile/Scrum development environments.
• Knowledge of the insurance or financial services domain is a strong advantage.
• Strong analytical, problem-solving, and solution-design capabilities.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts clearly.
• Comfortable working independently, managing priorities, and taking ownership of deliverables.
• Experience collaborating with multicultural and globally distributed teams.
• Bachelor's degree or equivalent qualification in Computer Science, Data Science, Engineering, or a related discipline is preferred.