Data Engineering (Palantir, Spark, PySpark, Python)- W2 Role
Job Description
Job Description
Job Title: Technical Lead Data Engineering (Palantir, Spark, PySpark, Python)
Please dont apply if you dont have PALANTIR experience Onsite work :One or two days in a monthW2 role
OPT with 7 years exp is fine Job Summary
We are looking for a hands-on Technical Lead in Data Engineering to drive the design, development, and delivery of scalable data solutions in a large retail enterprise. This role requires strong expertise in Palantir Foundry, Spark/PySpark, SQL, and Python, along with the ability to lead engineering teams and partner with business stakeholders across supply chain, merchandising, and store operations. Key Responsibilities
- Lead the design and implementation of scalable data platforms and pipelines using PySpark, Spark, and Python
- Drive adoption and best practices for Palantir Foundry (data pipelines, ontology, workflows, and operational applications)
- Architect and optimize high-performance data processing solutions for large-scale datasets
- Provide technical leadership and mentorship to data engineers, ensuring code quality and best practices
- Collaborate with cross-functional teams (business, analytics, data science) to translate requirements into scalable solutions
- Design robust data models, ETL/ELT frameworks , and data integration strategies
- Ensure data quality, governance, security, and compliance across enterprise data platforms
- Lead performance tuning, troubleshooting, and optimization of data pipelines
- Drive CI/CD implementation , code reviews, and release management
- Stay current with emerging data engineering technologies and recommend improvements
- Bachelors or Masters degree in Computer Science, Engineering, or related field
- 8+ years of experience in data engineering , with at least 23 years in a technical leadership role
- Strong hands-on experience with:
- Python & PySpark
- Apache Spark
- Advanced SQL
- Experience with Palantir Foundry or similar modern data platforms
- Deep understanding of data engineering principles (ETL/ELT, data modeling, distributed systems)
- Experience designing and managing large-scale data architectures
- Strong leadership, communication, and stakeholder management skills
- Experience in retail domain (supply chain, inventory, merchandising, store analytics)
- Experience with cloud platforms (Azure, AWS, or GCP)
- Familiarity with orchestration tools (Airflow, Azure Data Factory, etc.)
- Experience with real-time/streaming data pipelines
- Exposure to DevSecOps practices
- Technical Leadership
- Data Engineering Architecture
- PySpark & Spark
- Python Programming
- SQL Optimization
- Palantir Foundry
- Data Modeling & Warehousing
- CI/CD & DevOps
Flexible work from home options available.
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