Senior Data Platform Architect

Role Overview We are looking for a Senior Data Platform Architect to design and lead the implementation of a scalable, secure, and modern enterprise data platform. This role is central to our mission to enable real-time insights, machine learning at scale, and data democratization across the business. You will architect end-to-end data ecosystems — from ingestion to access — while driving standards that ensure trust, governance, and performance across domains. What You’ll Own Platform Strategy & Architecture Define and lead the data platform strategy, aligning with analytics, AI/ML, and business intelligence goals. Architect scalable solutions including lakehouse models, event-driven pipelines, and multi-cloud storage strategies. Technical Leadership Guide engineering teams in building robust batch and streaming data pipelines using best-in-class tools and frameworks. Define reference architectures, blueprints, and guardrails to enable repeatable, secure, and performant platform components. Modern Stack Enablement Evaluate and implement tools across data orchestration, transformation, lineage, cataloging, and observability — e.g., Airflow, dbt, Delta Lake, Kafka, Snowflake, Databricks. Governance by Design Embed data privacy, lineage, and access control into the platform’s core — enabling compliance with GDPR, HIPAA, and industry regulations. Cloud-Native Infrastructure Design cost-efficient, elastic architectures on AWS, Azure, or GCP using infrastructure-as-code (Terraform, CDK, etc.) Cross-Functional Alignment Partner with analytics, product, and infrastructure leaders to ensure the platform meets current and future business needs. Mentorship & Scale Uplift engineering maturity across the team via design reviews, architecture clinics, and hands-on mentorship. Requirements 8+ years in data engineering, architecture, or platform leadership roles Proven experience architecting large-scale distributed data platforms in cloud environments Strong expertise in data lake/lakehouse, streaming, and warehouse architectures Hands-on familiarity with tools such as Spark, Kafka, dbt, Airflow, Delta Lake, and cloud-native storage & compute (e.g., S3 + EMR / BigQuery / Synapse) Solid understanding of data modeling, cataloging, versioning, lineage, and access controls Excellent communication skills — able to influence at both engineering and executive levels Bachelor's or Master’s in Computer Science, Data Engineering, or a related field Preferred Qualifications Cloud certification (AWS Certified Data Analytics, GCP Professional Data Engineer, etc.) Experience deploying data platforms in regulated industries (banking, healthcare, public sector) Familiarity with data mesh, domain-driven design, or federated governance patterns Exposure to MLOps and integration of AI/ML workloads on data platforms Benefits Benefits & Growth Opportunities: ·       Competitive salary and performance bonuses ·       Comprehensive health insurance ·       Professional development and certification support ·       Opportunity to work on cutting-edge AI projects ·       International exposure and travel opportunities ·       Flexible working arrangements ·       Career advancement opportunities in a rapidly growing AI company This position offers a unique opportunity to shape the future of AI implementation while working with a talented team of professionals at the forefront of technological innovation. The successful candidate will play a crucial role in driving our company's success in delivering transformative AI solutions to our clients.