Birlasoft is Hiring Data Engineer - Palantir (Backend) | Bangalore

Job Description

Worth flagging upfront: this posting doesn't specify an explicit experience level or "fresher" framing anywhere in the text — no "0-2 years" or similar range is stated. Given the genuinely specialized technology involved (Palantir Foundry, PySpark at scale), this is worth treating with some caution regarding fresher-accessibility; it's plausible this role expects candidates with some prior hands-on data engineering experience despite the absence of an explicit years-of-experience statement. Worth confirming directly with the recruiter where this falls on the experience spectrum before investing significant application effort as a true fresher.

This listing centers on a genuinely specialized and less commonly available technology: 𝐏𝐚𝐥𝐚𝐧𝐭𝐢𝐫 𝐅𝐨𝐮𝐧𝐝𝐫𝐲. Palantir is a well-known but niche enterprise data platform, primarily used by large organizations for complex data integration and analytics. Genuine hands-on experience with Foundry is rare — it's not something typically covered in standard CS coursework or widely available through free online courses, unlike more common tools like Databricks or Snowflake. If you have any exposure to Palantir Foundry, this would be a significant differentiator given how uncommon that exposure is among the general applicant pool.

The core technical work is genuine large-scale 𝐝𝐚𝐭𝐚 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 — building PySpark-based batch processing pipelines, ETL/ELT workflows, and curated datasets, with attention to performance optimization, data quality, and governance/lineage tracking. This is substantive backend data engineering work, not entry-level data analysis or reporting — worth knowing that even without the Palantir-specific tooling, the underlying PySpark and data pipeline skills required here are genuinely advanced for a role without a clearly stated fresher framing.

𝐎𝐮𝐫 𝐓𝐚𝐤𝐞:

- 𝐆𝐨𝐨𝐝 𝐟𝐨𝐫: Candidates with genuine hands-on PySpark and data pipeline experience through internships, significant personal projects, or prior work, ideally with any exposure to Palantir Foundry specifically or similar enterprise data platforms.

- 𝐍𝐨𝐭 𝐢𝐝𝐞𝐚𝐥 𝐟𝐨𝐫: True freshers without any hands-on big data/PySpark project experience — given the absence of explicit fresher framing and the specialized, advanced nature of Palantir Foundry work, this likely isn't accessible to someone starting from purely theoretical coursework.

- 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲: 𝐋𝐢𝐤𝐞𝐥𝐲 𝐡𝐢𝐠𝐡 — Palantir Foundry expertise is genuinely rare in the general applicant pool, meaning candidates who do have any exposure would face less competition, but building that exposure without prior professional access to Foundry is itself a challenge.

- 𝐂𝐚𝐫𝐞𝐞𝐫 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲: Commonly leads into 𝐒𝐞𝐧𝐢𝐨𝐫 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫, Palantir Foundry Specialist, or Data Platform Architect roles — genuine Palantir experience is a distinctive credential given how few professionals have hands-on exposure to this specific platform.

𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: Birlasoft hasn't disclosed pay for this role, and the salary range field in the posting itself is left blank. Given the specialized nature of Palantir Foundry work, compensation for candidates with genuine hands-on experience could be meaningfully above typical fresher data engineering roles — general market data for specialized big data/Palantir roles suggests a range that could start around ₹6-10 LPA for early-career candidates with real PySpark/big data project experience, though this is a broad estimate given the ambiguity in this specific posting.

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: Given the specialized platform requirement, if you don't have direct Palantir Foundry experience, lead with your strongest 𝐏𝐲𝐒𝐩𝐚𝐫𝐤 and large-scale data pipeline project work instead — even a personal project processing large datasets with Spark, or coursework involving ETL pipeline design, would be relevant; and directly ask the recruiter during initial screening whether prior Foundry experience is truly required or whether strong PySpark/data engineering fundamentals with willingness to learn Foundry specifically would be considered, since the posting itself doesn't clarify this.

Roles & Responsibilities

The responsibilities center on building and maintaining production-grade data infrastructure specifically within the Palantir Foundry platform.

- Design and build scalable data pipelines using PySpark for large-scale batch processing

- Develop ETL/ELT workflows within Palantir Foundry

- Build and maintain curated datasets, semantic models, and reusable data assets

- Optimize Spark jobs for performance, scalability, and cost efficiency

- Implement data quality checks, validation frameworks, and monitoring pipelines

- Work with data governance, lineage, and metadata management in Foundry

Qualifications & Eligibility

No explicit years-of-experience requirement is stated — worth clarifying this directly given the specialized technical scope described.

- Bachelor's or Master's degree in Computer Science, Information Systems, or equivalent experience

Skills Required

Highly specific and specialized, centered entirely on PySpark and the Palantir Foundry ecosystem.

- PySpark for large-scale batch data processing

- ETL/ELT workflow development within Palantir Foundry

- Spark job performance optimization

- Data quality validation and monitoring pipeline implementation

- Data governance, lineage, and metadata management (Foundry-specific)