Platform Engineer

ROLE OVERVIE

WWe are seeking an experienced Data Platform Lead for designing and implementation of an enterprise grade, AI-ready data platform — spanning cloud storage, data engineering pipelines, governance-ready data products, and GenAI / RAG workloads. The ideal candidate brings deep expertise with AWS-native services, Databricks, and modern data stack tools, with a strategic mindset to architect platforms delivering governed, AI consumable datasets at scale

KEY RESPONSIBILITI

ES1. Storage & Platform Foundati onArchitect the AWS Data Platform: Amazon S3, Athena, Redshift, and AWS Lake Formation for governed acce ssDesign and operate Databricks Lakehouse (Delta Lake, Unity Catalog, Databricks Comput e)Ensure secure, scalable, and cost-optimized foundational infrastructure aligned to enterprise SL erLead data engineering pipelines using dbt (transformations & modeling) and Databricks (ML Runtime, Notebook s)Implement Data Quality & Testing using SODA; design Workflow Orchestration with monitoring and alerti ngDrive a shift-left engineering culture with reusable, well-documented pipeline 3. Data Products Layer — AI-Ready Datase tsDefine and build domain-owned, AI-ready Data Products (Customer 360, Patient 360, Clinical, Commercial, Feature-Ready, and RAG-Ready dataset s)Champion a Data Mesh / Data Product mindset with clear ownership, SLAs, and discoverabili ty4. Governance & Catalog Lay erImplement unified data governance using Atlan (Governance & Catalog) for discoverability, lineage, trust, and contr olEstablish end-to-end Data Lineage tracking (data to production) using classification taggi ngDefine and enforce Policies & Access controls: RBAC/ABAC, PII/PHI tagging, sensitive data classification, and policy enforceme ntDrive AI Governance practices: AI data usage policies, model lineage, bias detection, and audit readine ssEnsure Quality & Trust standards: data quality SLAs, certification workflows, and DQ dashboar ds5. AI & Advanced Analytics Enableme ntArchitect data infrastructure supporting ML Models (predictive, prescriptive, optimization) and GenAI/RAG pipelin esDesign pipelines for LLM apps, copilots, and knowledge search; support real-time Decision Syste msCollaborate with domain teams to build Domain-Owned AI & ML models on governed, trusted da ta6. Cross-Cutting Capabiliti esSecurity & Compliance: End-to-end data security, IAM, encryption, and audit-ready regulatory compliance (HIPAA, GDPR, SOC 2)Monitoring & Observability: Platform-level data and model observability, pipeline health dashboar dsCollaboration: Tools and practices to connect people, knowledge, and data across the organizati

REQUIRED SKILLS & QUALIFICATI

rage10+ years of experience in data architecture and cloud platf ormsDeep expertise with AWS services: S3, Athena, Redshift, Lake Formation, Glue, IAMProficiency in Databricks: Delta Lake, Unity Catalog, Databricks Workflows, ML flowExperience with data lakehouse architecture patterns and medallion architecture (Bronze / Silver / G ationStrong hands-on expertise with dbt (data build tool) for SQL-based transformations and data modelingPipeline orchestration experience: Apache Airflow, Databricks Workflows, or equiv alentData quality tooling: SODA, Great Expectations, or Monte CarloProficiency in Python, SQL, and Spark Spark Data Governance & C atalogExperience implementing data catalogs and governance tools (Atlan, Collibra, Alation, or equiv alent)Knowledge of data lineage, metadata management, classification fram eworksUnderstanding of RBAC/ABAC, PII/PHI regulations, and policy enforcement at the platform level AI & GenAI Re adinessExperience building Feature Stores and ML-ready datasets for model training and inf erence.Familiarity with RAG (Retrieval-Augmented Generation) architecture: chunking, embedding generation, vector storesUnderstanding of LLMOps, model observability, and AI governance fra meworksExperience with vector databases (Pinecone, Weaviate, pgvector, or Databricks Vector adershipProven ability to design and document enterprise data architecture using frameworks like TOGAF or ZachmanStrong stakeholder engagement skills — ability to translate business needs into technical arch itectureExperience working in regulated industries (Life Sciences, Financial Services, Healthcare) is a str ong plusAWS Certified Solutions Architect (Professional) or Databricks Certified Professional p referred NIC E TO HAVE Experience with ThoughtSpot, Tableau, or Power BI for self-service BI layer i ntegrationFamiliarity with SAS Viya or clinical analytics platformsKnowledge of FHIR, HL7, or CDISC data standards for Lif e SciencesContributions to open-source data engineerin g projectsExperience with multi-cloud or hybrid-cloud arc

AT WE OFFER

Opportunity to architect one of the most comprehensive AI-ready data platforms in AT WE OFFER the industry Exposure to Fortune 500 clients across Life Sciences, Financial Services, and Technology AWS Generative AI Competency partner — work on cutting-edge GenAI and L LM use casesCollaborative, innovation-first culture with clear career growth pathCompetitive compensation, flexible work arrangements (remote/hybri d available)Access to certifications, training, and industry conferencesComprehensive Benefits: Medical, Dental, and Vision insurance coverage for employees and eligible dependents.Retirement Benefits: 401(k) retirement savings plan with company benefits as #J-18808-Ljbffr USEFULBI TECHNOLOGY