Lead Architect - Data Engineer

Fractal Analytics · Bengaluru

  • Experience11–15 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted2 Sept 2026
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About Fractal Analytics

Fractal Analytics is hiring in Bengaluru in technology software. This role looks for around 11+ years of experience.

Skills

  • Google Cloud Platform
  • data engineering
  • cloud-native technologies
  • big data
  • analytics
  • AI/ML
  • BigQuery
  • Cloud Composer
  • Dataflow
  • Cloud Storage
  • Vertex AI
  • Dataproc
  • GCP IaaS
  • Python
  • Java
  • Agile
  • CI/CD
  • DevOps
  • MLOps
  • technical architecture
  • microservices
  • event-driven architecture
  • event streaming
  • online machine learning

The role

A data architect at a technology software company defines Google Cloud Platform architectures for data engineering, analytics, and AI/ML solutions, using BigQuery and Vertex AI to build scalable platforms and guides microservices and MLOps practices.

Full job description

Responsibilities:

Evaluate the current technology landscape and recommend a forward-looking, short-term, and long-term technology strategic vision.

You will participate in the creation and sharing of best practices, technical content, and new reference architectures.

Work with data engineers and data scientists to develop architectures and solutions.

Assist in ensuring the smooth delivery of services/products and solutions.

Requirements:

In-depth experience as an architect who has experience in Google Cloud Platform and is passionate about applying the latest technologies to solve business problems.

11+ years of experience in data engineering and cloud-native technologies (including Google Cloud Platform) that cover the big data, analytics and AI/ML domains are essential, with experience using GCP.

Experience in BigQuery, Cloud Composer, Data Flow, Cloud Storage, AI Platform/Vertex AI, Dataproc, GCP IaaS. Creating, deploying, configuring, and scaling applications on GCP serverless infrastructure.

Knowledge and working experience in data engineering, data management and data governance.

Experience working in multiple end-to-end data engineering and/or analytics projects.

Knowledge of general programming languages and frameworks, in particular Python and/or Java.

General technology best practices and development lifecycles, such as agile and CI/CD, and also those enabling more efficient employment of data and machine learning, such as DevOps and MLOps.

Technical architecture leadership and direction on projects resulting in secure, scalable, reliable, and maintainable platforms.

Architecture skills that enable the creation of future-proof, complex global solutions using GCP services.

Implementation and/or creation of foundational architectures, including microservices, event-driven and event streaming, and those that enable online machine learning systems.

Excellent communication and influencing skills, being able to adapt according to the target audience.

Good to have:

Experience in container technology, specifically Docker and Kubernetes, and DevOps on GCP.

Google Cloud - Professional Cloud Architect Certification.