Palantir Engineer_2+ years

Zorba AI

Maharashtra

Sur place

INR 700 000 - 1 200 000

Plein temps

Il y a 4 jours
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Résumé du poste

Zorba AI is seeking a Data Engineer in Maharashtra with 2+ years of PySpark, Python and SQL experience and hands-on Palantir Foundry expertise. You will design and implement data analytics solutions on enterprise data platforms and distributed computing environments such as Spark, Hive, or Hadoop.

Strong data modelling, transformation, and end-to-end data management skills are required to deliver analytics-ready data pipelines.

Qualifications

  • 2+ years of experience in data engineering with PySpark, Python and SQL.
  • Hands-on experience with Palantir Foundry platform.
  • Strong understanding of data modelling, transformation and end-to-end data management.

Responsabilités

  • Design and implement data analytics solutions on enterprise data platforms.
  • Build scalable, reliable data pipelines for analytics and reporting.
  • Translate customer requirements into data architecture and technical designs.

Connaissances

PySpark
Python
SQL
Data modelling
Data transformation
Data pipelines
SQL (Spark SQL)

Outils

Palantir Foundry
Spark
Hive
Hadoop

Description du poste

We are looking for a Data Engineer with 2+ years of experience in PySpark, Python, and SQL, along with mandatory hands-on experience with the Palantir Foundry platform. The candidate should have experience designing and implementing data analytics solutions on enterprise data platforms and distributed computing environments such as Spark, Hive, or Hadoop. Strong knowledge of data modelling, data transformation, and end-to-end data management for analytical use cases is required. The role involves understanding customer requirements and translating them into best-fit technical designs and data architecture. Candidates should be proficient in SQL, preferably Spark SQL, and have experience building scalable, reliable, and high-quality data pipelines for enterprise analytics and reporting requirements.
Skills: palantir,sql,pyspark

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