We are seeking a hands-on Data Platform Architect to lead the design, implementation, and modernization of our enterprise-wide data platform鈥攊ncluding data governance, lakehouse architecture, engineering pipelines, analytics, and AI-driven solutions. This role requires deep technical expertise, strategic vision, and executional leadership to build a scalable, governed, and intelligent data ecosystem across cloud and on-prem environments.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
Architecture & Strategy
- Define and continuously evolve the target data architecture across the stack鈥攇overnance, engineering, modeling, lakehouse, AI/ML.
- Translate business and technical goals into scalable and resilient platform designs.
- Own and maintain architectural roadmaps, standards, and decision frameworks.
- Act as the bridge between architects, Business SME/Analysts, data engineers, and analytics teams to ensure alignment and compliance with platform standards.
Data Engineering & Platform Delivery
- Design and implement modern ELT/ETL pipelines using tools like Spark, Python, SQL, Scala, and cloud-native components (e.g., Fivetran, Databricks, Snowflake, BigQuery).
- Proven Hand-on experience in Databricks & Unity Catalogue.
- Build and maintain Lakehouse platforms using Delta Lake, Iceberg, or equivalent technologies.
- Manage data ingestion from heterogeneous sources including ERP, CRM, IoT, and third-party APIs.
- Guide hands-on development of robust, reusable, and automated data flows.
Governance, Metadata, and Quality
- Implement and enforce data governance frameworks including data lineage, metadata management, and access controls.
- Partner with Data Stewards and Governance Analysts to catalog data domains, define entities, and ensure SOX compliance.
- Drive adoption of tools like and Atlan/Unity Catalog for metadata, quality, and stewardship.
- Develop data models (ERDs, dimensional and 3NF) and define canonical data representations.
Collaboration & Leadership
- Review solution designs and provide architectural guidance to engineering teams.
- Mentor technical staff while fostering best practices and continuous improvement.
- Collaborate with DevOps to embed CI/CD, version control, and environment automation across the data lifecycle.
- Continuously assess and improve platform reliability, scalability, performance, and cost-efficiency.