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.