‍

Please find below the details of the role and its responsibilities.

Skills Required:

Terraform, Kafka, Delta Lake, Deltalake, Data Architect, Data Architecture, Platform

Architect, Agentic AI, AI Models, CI/CD, CI-CD, CICD

Experience Range:

8 - 12 years

‍

Job Description:

Senior Architect, Systems – Data Ingest Engineering

‍

About the Role

Data Ingest Engineering is the central engineering team building the Enterprise Unified

Ingestion Framework for the future that delivers the right data, at the right speed, with the

right governance — to every consumer: a customer opening an app, a business

analyst asking a natural language question, or an AI agent executing autonomously.

‍

As a Senior Architect, Systems, you will define and own the architectural patterns that

make the Unified Ingestion Framework scale — designing and delivering the batch and

streaming framework for how data flows from a source system to the Lakehouse. We

pride ourselves on fostering a culture of innovation, agile ways of working, and

transparency in everything we do. Join us in embodying the spirit of the Un-carrier and

make a tangible impact!

‍

‍What You’ll Do:

• Define and own the reference architecture for data ingestion framework for

both batch and streaming.

• Design and set technical standards for high-throughput, event-driven architectures to

power near real-time data pipelines for ingesting into Azure + Databricks Lakehouse.

• Architect AI capabilities to enhance and optimize the Unified Ingestion Framework.

• Partner with peer architects across Serving, Data Product, Semantic Layer,

Governance, and Platform Engineering to ensure end-to-end coherence.

• Define SLAs, SLOs, and observability standards with SREs for data ingest

infrastructure.

• Design Infrastructure-as-Code standards in repeatable, governed way.

• Lead architecture reviews, evaluate emerging technologies, and recommend platform

investments.

• Mentor engineers and raise the architectural capability of the team.

‍

What You’ll Bring:

• 7+ years of systems engineering and architecture experience, including data platforms

and large-scale distributed systems.

• Proven track record defining reference architectures for data integration in enterprise

environments.

• Deep expertise in data platform architecture: Lakehouse patterns, Delta Lake, Unity

Catalog, and modern data product design.

• Hands-on knowledge of streaming architectures (Kafka, Redis, CDC, event-driven

serving).

• Hands-on experience with the Microsoft Azure data platform — Azure Data Factory,

Event Hubs, Blob Storage, ADLS Gen2, and Azure DevOps for orchestration and

CI/CD

• Proven experience with Infrastructure as Code (Terraform or comparable)

• Strong communication skills with the ability to influence senior stakeholders and lead

technical decisions across global teams.

‍

Must Have Skills:

• Data Platform Architecture (Lakehouse, Delta Lake, Azure Databricks)

• Kafka / Streaming Frameworks• Infrastructure as Code and CI/CD

• Experience with Cloud Native Tools

Nice-to-Have:

• Building data infrastructure for AI use cases

• Prior architecture leadership in large enterprise data integration or data platform

engineering environments

• Prior experience in enterprise platform migrations

‍