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 rolesProven experience architecting large-scale distributed data platforms in cloud environmentsStrong expertise in data lake / lakehouse, streaming, and warehouse architecturesHands-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 controlsExcellent communication skills — able to influence at both engineering and executive levelsBachelor's or Master’s in Computer Science, Data Engineering, or a related fieldPreferred 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 patternsExposure to MLOps and integration of AI / ML workloads on data platformsBenefits
Benefits & Growth Opportunities :
Competitive salary and performance bonusesComprehensive health insuranceProfessional development and certification supportOpportunity to work on cutting-edge AI projectsInternational exposure and travel opportunitiesFlexible working arrangementsCareer advancement opportunities in a rapidly growing AI companyThis 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.