Job description
<p><p><b>Position Title :</b> Data Architect Data Engineering<br/><br/><b>Scope Of Responsibility :</b></p><p><br/></p><p>As a Data Architect Data Engineering, you will play a key role in shaping Client Life Science's 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.<br/><br/></p><p>You will lead design efforts and provide architectural governance across data ingestion, transformation, storage, and consumption layersensuring seamless interoperability across platforms while enabling compliance, performance, and & Responsibilities :</b></p><p><b><br/></b></p>- Design and maintain an integrated data architecture that connects Palantir Foundry, AWS services, and Snowflake, ensuring secure, scalable, and performant data access.<br/><br/></p><p>- Define and govern enterprise-wide standards for data modeling, metadata, lineage, and security across hybrid environments.<br/><br/></p><p>- Architect high-throughput data pipelines that support batch and real-time ingestion from APIs, structured/unstructured sources, and external platforms.<br/><br/></p><p>- Collaborate with engineering, analytics, and product teams to implement analytical-ready data layers across Foundry, Snowflake, and AWS-based lake houses.<br/><br/></p><p>- Define data optimization strategies including partitioning, clustering, caching, and materialized views to improve query performance and reduce cost.<br/><br/></p><p>- Ensure seamless data interoperability across Palantir objects (Quiver, Workshop, Ontology), Snowflake schemas, and AWS S3-based data lakes.<br/><br/></p><p>- Lead DataOps adoption including CI/CD for pipelines, automated testing, quality checks, and monitoring.<br/><br/></p><p>- Govern identity and access management using platform-specific tools (e.g., Foundry permissioning, Snowflake RBAC, AWS IAM).<br/><br/></p><p>- Drive compliance with data governance frameworks, including auditability, PII protection, and regulatory requirements (e.g., GxP, HIPAA).<br/><br/></p><p>- Evaluate emerging technologies (e.g., vector databases, LLM integration, Data Mesh) and provide recommendations.<br/><br/></p><p>- Act as an architectural SME during Agile Program Increment (PI) and Sprint Planning sessions.<br/><br/><b>Education & Certifications :</b></p><p><p><b><br/></b></p>- Bachelors or Masters degree in Computer Science, Data Engineering, or a related field.<br/><br/></p><p>- AWS/ Palantir/ Snowflake Architect or Data Engineer Certification (preferred).<br/><br/><b>Experience :</b></p><p><p><b><br/></b></p>- 6- 8 Years of data engineering and architecture experience</p><p><br/></p><p>- Hands-on experience with Palantir Foundry (Quiver pipelines, Workshop, Ontology design).</p><p><br/></p><p> - Working knowledge on AWS data services (S3, Glue, Redshift, Lambda, IAM, Athena).<br/><br/></p><p> - Working with Snowflake (warehouse design, performance tuning, secure data sharing).<br/><br/></p><p> - Domain experience in life Science/Pharma or regulated environments preferred.<br/><br/><p><b>Technical Skills :</b></p><p><b><br/></b></p>- Data Architecture : Experience with hybrid data lake/data warehouse architecture, semantic modeling, and consumption layer design.<br/><br/></p><p>- Palantir Foundry : Proficiency in Quiver pipelines, Workshop applications, Ontology modeling, and Foundry permissioning.<br/><br/></p><p>- Snowflake : Deep understanding of virtual warehouses, time travel, data sharing, access controls, and cost optimization.</p><p><br/>- AWS : Strong experience with S3, Glue, Redshift, Lambda, Step Functions, Athena, IAM, and monitoring tools (e.g., CloudWatch).<br/><br/></p><p>- ETL/ELT : Strong background in batch/streaming data pipeline development using tools such as Airflow, dbt, or NiFi.<br/><br/></p><p>- Programming : Python, SQL (advanced), Shell scripting; experience with REST APIs and JSON/XML formats.<br/><br/></p><p>- Data Modeling : Dimensional modeling, third-normal form, NoSQL/document structures, and modern semantic modeling.<br/><br/></p><p>- Security & Governance : Working knowledge of data encryption, RBAC/ABAC, metadata catalogs, and data classification.</p><p><br/>- DevOps & DataOps : Experience with Git, Jenkins, Terraform/CloudFormation, CI/CD for data workflows, and observability tools.<br/><br/><b>Soft Skills :</b></p><p><p><b><br/></b></p>- Strategic and analytical thinking with a bias for action.<br/><br/></p><p>- Strong communication skills to articulate architecture to both technical and business audiences.<br/><br/></p><p>- Ability to work independently and collaboratively in cross-functional, global teams.<br/><br/></p><p>- Strong leadership and mentoring capability for junior engineers and architects.<br/><br/></p><p>- Skilled in stakeholder management, technical storytelling, and influencing without authority.<br/><br/><b>Good-to-have Skills :</b></p><p><p><b><br/></b></p>- Experience with Data Mesh or federated governance models.<br/><br/></p><p>- Integration of AI/ML models or LLMs with enterprise data architecture.<br/><br/></p><p>- Familiarity with business intelligence platforms (e.g., Tableau, Power BI) for enabling self-service analytics.<br/><br/></p><p>- Exposure to vector databases or embedding-based search systems.<br/><br/>At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment.
We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.</p><br/></p> (ref:hirist.tech)
Required Skill Profession
Computer Occupations