Cloud Data Architect Lead

7 days ago

Mumbai, Maharashtra, India beBeeData Full time
Cloud Data Architect Role

We are seeking a seasoned Cloud Data Architect to design, implement, and champion scalable, secure data architectures in cloud environments. The ideal candidate will be a technical expert who not only drives delivery excellence but also collaborates with sales and pre-sales teams to create assets and artifacts that support business development and client acquisition.

Main Responsibilities
  • Design and build robust cloud-based data platforms, including data lakes, data warehouses, and real-time data pipelines.
  • Ensure data quality, consistency, and security across all systems and projects.
  • Work closely with cross-functional teams to integrate diverse data sources into a cohesive and performant architecture.
Sales & Pre-Sales Support
  • Serve as a technical advisor in sales engagements to develop and articulate compelling cloud data solutions.
  • Create reusable assets, solution blueprints, and reference architectures to support RFP responses and sales proposals.
  • Present technical roadmaps and participate in client meetings to demonstrate the value of our solutions to prospective clients.
Cross-Functional Collaboration
  • Act as a liaison between technical delivery and sales teams to ensure a seamless alignment of strategies.
  • Mentor team members and lead technical discussions on architecture best practices.
Required Qualifications
  • A Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
  • Extensive experience in data architecture and design within cloud environments.
  • A proven track record of supporting pre-sales initiatives and business development.
  • Demonstrated experience with cloud data platforms and big data technologies.
  • Strong analytical, problem-solving, and communication skills.
Key Skills & TechnologiesMust-Have
  • Cloud Platforms: Proficiency in AWS, Azure, or Google Cloud.
  • Data Warehousing & Data Lakes: Hands-on experience with technologies like Redshift, BigQuery, or Snowflake.
  • Big Data Technologies: Experience with Hadoop, Spark, and Kafka.
  • Databases: Strong skills in both SQL & NoSQL databases.
  • ETL/ELT: Expertise in using various tools and pipelines.
  • Data Modeling: Advanced knowledge of data modeling and architecture design.
Good-to-Have
  • Infrastructure-as-Code (IaC): Familiarity with Terraform or CloudFormation.
  • Containerization: Experience with Docker and Kubernetes.
  • Programming: Proficiency in Python, Java, or Scala.
  • Data Governance: Knowledge of data governance and security best practices.

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