Cloud Architect

Description

At Sequoia Connect , we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a global IT powerhouse that represents the connected world through innovative, customer-centric experiences. As a USD 6 billion organization and one of the top 7 IT service providers globally, our client empowers over 1,200 global customers—including several Fortune 500 companies—to "Rise™." With a massive network of 163,000+ professionals across 90 countries, they are at the absolute forefront of digital transformation, leveraging next-generation technologies such as 5G, AI, Blockchain, and Quantum Computing.

This is your chance to thrive in a workplace recognized as one of the most sustainable corporations in the world. You will join an environment that values innovation and societal impact, working on end-to-end digital transformation projects for global leaders. If you are a driven professional looking for global career opportunities and exposure to high-impact projects within an international network of expertise, this is where you belong.

We are currently searching for a Cloud Architect :
Responsibilities

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End-to-End Architecture Design: Design and implement robust Lakehouse and Medallion architectures (Bronze, Silver, Gold layers) ensuring reliable, production-ready data pipelines.

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Performance Tuning & Optimization: Relentlessly troubleshoot, monitor, and tune large-scale Apache Spark jobs utilizing advanced techniques like caching, partitioning, and broadcast joins.

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Data Governance & Security: Design and deploy unified governance models for data and AI assets across the enterprise using Unity Catalog, implementing role-based access control (RBAC), row/column-level security, and comprehensive data lineage.

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Cloud Infrastructure Management: Integrate Databricks seamlessly within native cloud ecosystems (AWS, Azure, or GCP), configuring Virtual Networks (VNet) and robust IAM roles (e.g., ADLS/Entra, S3/IAM).

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Cost & Cluster Optimization: Proactively monitor and optimize Databricks Units (DBUs), right-size serverless and multi-node clusters, and implement best practices to prevent cloud bill shock and maximize ROI.

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Delta Lake Management: Leverage Delta Lake capabilities to manage ACID transactions, schema enforcement, time travel, and advanced optimization operations such as Z-ordering.

Requirements

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Experience: 5+ years of proven track record as a Cloud Architect, Principal Data Engineer, or similar role with a heavy focus on modern cloud data architectures and distributed computing.

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Databricks & Spark Mastery: Deep, under-the-hood understanding of Databricks, Apache Spark internals, and the Lakehouse Platform.

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Coding Proficiency: Advanced fluency in SQL, combined with expert-level programming skills in Python or Scala.

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Cloud Expertise: Strong grasp of native cloud ecosystems (AWS, Azure, or GCP) regarding networking, storage, and security.

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High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery within high-stakes data environments.

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Technologist DNA: A deep understanding of the difference between "coding" and "engineering" (knowing not just how to process data, but how to architect scalable, secure, and cost-efficient distributed systems).

Desired

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Certifications: Holding valid Databricks Certified Data Architect or Databricks Certified Data Engineer Professional badges is highly preferred.

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AI & ML Integration: Experience building, deploying, and monitoring GenAI applications and ML models using Databricks Model Serving, Vector Search, and the Mosaic AI suite.

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DevOps & CI/CD: Experience automating Databricks workflows using Git (Databricks Repos) and orchestration tools like dbt, Azure Data Factory, or Apache Airflow.

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Streaming Data: Familiarity with Databricks Structured Streaming and Auto Loader for real-time data ingestion and processing.

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Data Warehousing & BI: Understanding of Databricks SQL, Serverless Warehouses, and integration with downstream BI tools like Power BI.

- Familiarity with cloud-native foundations or AI coding assistants.

Languages

- Advanced Oral English.

- Advanced Spanish.

Note:
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 Fully remote

If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page :

Originally posted on Himalayas