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.