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Weekday AI · Presencial · Pune, Maharashtra, India

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟳𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟵𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟳-𝟵 𝗟𝗣𝗔)

Experience: 3+ yrs

Location: Pune, Maharashtra, India

Job Type: Full-time

We are looking for a talented Palantir Foundry Developer with strong expertise in Palantir Foundry, Azure Databricks, and Azure Data Lake to build and optimize modern enterprise data platforms. This role is ideal for professionals who enjoy designing scalable data solutions, developing robust data pipelines, and enabling data-driven decision-making through cloud-based analytics platforms.

As a Palantir Foundry Developer, you will collaborate with data engineers, solution architects, business analysts, and cross-functional stakeholders to deliver high-quality data integration and transformation solutions. You will play a key role in designing data workflows, managing enterprise data assets, and implementing scalable data models that support analytics, reporting, and operational excellence. The role offers an opportunity to work with cutting-edge cloud technologies while contributing to large-scale digital transformation initiatives in a collaborative environment.

Requirements

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines using Palantir Foundry and Azure-based data platforms.
  • Build, optimize, and manage data transformation workflows to process structured and unstructured data efficiently.
  • Develop and maintain data ingestion, integration, and orchestration pipelines using Azure Databricks.
  • Implement and manage enterprise data storage solutions using Azure Data Lake while ensuring data quality and consistency.
  • Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable technical solutions.
  • Design reusable data models, datasets, and analytical pipelines that support reporting and business intelligence initiatives.
  • Optimize data processing performance, pipeline reliability, and overall platform efficiency.
  • Troubleshoot data integration issues, monitor workflow execution, and resolve production incidents in a timely manner.
  • Implement data governance, security, and access control best practices across enterprise data assets.
  • Create and maintain technical documentation for data architecture, workflows, and deployment processes.
  • Participate in code reviews, testing activities, and continuous improvement initiatives to ensure high-quality deliverables.
  • Stay updated with emerging technologies and best practices related to cloud data engineering and analytics.

What Makes You a Great Fit

  • 3+ years of experience in Data Engineering or Cloud Data Platform Development.
  • Strong hands-on expertise in Palantir Foundry, including data pipelines, ontology, code repositories, and workflow development.
  • Experience working with Azure Databricks, Spark, and distributed data processing frameworks.
  • Strong knowledge of Azure Data Lake, cloud storage, and enterprise data management.
  • Proficiency in SQL, Python, and data transformation techniques for large-scale datasets.
  • Good understanding of ETL/ELT processes, data modeling, data integration, and workflow orchestration.
  • Experience working with cloud-based data platforms and modern analytics architectures.
  • Strong analytical, debugging, and problem-solving skills with attention to detail.
  • Excellent communication and collaboration skills with the ability to work effectively across cross-functional teams.
  • Familiarity with Azure ecosystem services, DevOps practices, CI/CD pipelines, and data governance frameworks will be an added advantage.
  • A proactive mindset with a passion for building scalable, secure, and high-performing enterprise data solutions.
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At Weekday (backed by YC; also Product Hunt #1 product of the day), we are building the next frontier in hiring. We have built the largest database of white collar talent in India and have built outreach tools on top of it to generate highest response rates.

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