Senior Data Engineer - Palantir

We are looking forward to hire Palantir Professionals in the following areas :

Experience required: 6-8 years

Position Title: Data Architect - Data Engineering
Location: Bangalore

SCOPE OF RESPONSIBILITY:

As a Data Architect - Data Engineering , you will play a key role in shaping clients Life Sciences modern data ecosystem that integrates Palantir Foundry , AWS cloud services , and Snowflake . Your responsibility will be to architect scalable, secure, and high-performing data pipelines and platforms that power advanced analytics, AI/ML use cases, and digital solutions across the enterprise.

You will lead design efforts and provide architectural governance across data ingestion, transformation, storage, and consumption layers-ensuring seamless interoperability across platforms while enabling compliance, performance, and cost-efficiency.

PURPOSE OF THE POSITION:

The role aims to define and implement future-ready, cloud-native, and platform-agnostic data architecture that unifies business, scientific, and operational data assets. You will enable clients Life Science organization to make informed, data-driven decisions at scale, while ensuring architectural alignment with security, governance, and business agility.

ROLES RESPONSIBILITIES:

• Design and maintain an integrated data architecture that connects Palantir Foundry , AWS services , and Snowflake , ensuring secure, scalable, and performant data access.
• Define and govern enterprise-wide standards for data modeling, metadata, lineage, and security across hybrid environments.
• Architect high-throughput data pipelines that support batch and real-time ingestion from APIs, structured/unstructured sources, and external platforms.
• Collaborate with engineering, analytics, and product teams to implement analytical-ready data layers across Foundry, Snowflake, and AWS-based lake houses.
• Define data optimization strategies including partitioning, clustering, caching, and materialized views to improve query performance and reduce cost.
• Ensure seamless data interoperability across Palantir objects (Quiver, Workshop, Ontology), Snowflake schemas, and AWS S3-based data lakes.
• Lead DataOps adoption including CI/CD for pipelines, automated testing, quality checks, and monitoring.
• Govern identity and access management using platform-specific tools (e. g. , Foundry permissioning, Snowflake RBAC, AWS IAM).
• Drive compliance with data governance frameworks, including auditability, PII protection, and regulatory requirements (e. g. , GxP, HIPAA).
• Evaluate emerging technologies (e. g. , vector databases, LLM integration, Data Mesh) and provide recommendations.
• Act as an architectural SME during Agile Program Increment (PI) and Sprint Planning sessions.

EDUCATION CERTIFICATIONS:

• Bachelor s or Master s degree in Computer Science, Data Engineering, or a related field.
• AWS/ Palantir/ Snowflake Architect or Data Engineer Certification (preferred).

EXPERIENCE:

• 6-8 Years of data engineering and architecture experience, with at least:

• • • • Hands-on experience with Palantir Foundry (Quiver pipelines, Workshop, Ontology design).
      • Working knowledge on AWS data services (S3, Glue, Redshift, Lambda, IAM, Athena).
      • Working with Snowflake (warehouse design, performance tuning, secure data sharing).

• Domain experience in life Science/Pharma or regulated environments preferred.

TECHNICAL SKILLS:

• Data Architecture: Experience with hybrid data lake/data warehouse architecture, semantic modeling, and consumption layer design.
• Palantir Foundry: Proficiency in Quiver pipelines, Workshop applications, Ontology modeling, and Foundry permissioning.
• Snowflake: Deep understanding of virtual warehouses, time travel, data sharing, access controls, and cost optimization.
• AWS: Strong experience with S3, Glue, Redshift, Lambda, Step Functions, Athena, IAM, and monitoring tools (e. g. , CloudWatch).
• ETL/ELT: Strong background in batch/streaming data pipeline development using tools such as Airflow, dbt, or NiFi.
• Programming: Python, SQL (advanced), Shell scripting; experience with REST APIs and JSON/XML formats.
• Data Modeling: Dimensional modeling, third-normal form, NoSQL/document structures, and modern semantic modeling.
• Security Governance: Working knowledge of data encryption, RBAC/ABAC, metadata catalogs, and data classification.
• DevOps DataOps: Experience with Git, Jenkins, Terraform/CloudFormation, CI/CD for data workflows, and observability tools.

SOFT SKILLS:

• Strategic and analytical thinking with a bias for action.
• Strong communication skills to articulate architecture to both technical and business audiences.
• Ability to work independently and collaboratively in cross-functional, global teams.
• Strong leadership and mentoring capability for junior engineers and architects.
• Skilled in stakeholder management, technical storytelling, and influencing without authority.

GOOD-TO-HAVE SKILLS:

• Experience with Data Mesh or federated governance models.
• Integration of AI/ML models or LLMs with enterprise data architecture.
• Familiarity with business intelligence platforms (e. g. , Tableau, Power BI) for enabling self-service analytics.
• Exposure to vector databases or embedding-based search systems.

Our Hyperlearning workplace is grounded upon four principles

• Flexible work arrangements, Free spirit, and emotional positivity
• Agile self-determination, trust, transparency, and open collaboration
• All Support needed for the realization of business goals,
• Stable employment with a great atmosphere and ethical corporate culture