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Open nowPosted yesterday

Solution Architect-Data Platforms

IBM2,390 open roles

Where
Bangalore, IN
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Your applicationOpen nowSolution Architect-Data PlatformsIBM · Bangalore, IN

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. IBM postings stay open a median of 6 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.2%30 days
This job: posted yesterday

IBM median: 6 days open

The posting

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

As a seasoned Solution Architect specializing in Data Platforms, you design end-to-end Big Data Solutions across various platforms, leveraging your extensive experience in managing large data repositories. You possess a deep understanding of industry standards, best practices, and key technologies such as the HADOOP Framework and Cloud native platforms.

Your primary responsibilities will include:

• Design End-to-End Solutions: Create tailored data solutions for clients, utilizing Cloud and traditional data platform offerings, and oversee the architecture for data platform and cognitive components.

• Develop Data Strategies: Leverage expertise in managing large data repositories to develop effective data management strategies, incorporating industry standards and best practices.

• Oversee Architecture: Guide the architecture for data platform and cognitive components, including unstructured data technologies, annotation, and related data and analytics.

• Collaborate with Clients: Work closely with clients to understand their needs and deliver customized data solutions that meet their requirements.

• Drive Technical Excellence: Stay up-to-date with emerging trends and technologies, applying deep expertise in data platforms to drive technical excellence and innovation.

• Deep Expertise in Data Platforms: Proven experience designing end-to-end Big Data Solutions across various platforms, with extensive expertise in managing large data repositories (terabyte scale or larger).

• Industry Standards and Best Practices: In-depth knowledge of industry standards, best practices, and key technologies such as the HADOOP Framework, Ecosystem, MapReduce, and Data on Containers (data in OpenShift).

• Cloud Native Platforms: Experience with Cloud native platforms such as AWS, Azure, Google, IBM Cloud, or Cloud Native data platforms like Snowflake, with the ability to leverage these platforms to create tailored data solutions.

• Unstructured Data Technologies: Strong understanding of unstructured data technologies, annotation, and related data and analytics, with the ability to guide the architecture for data platform and cognitive components.

• Data Management Strategies: Proven ability to develop effective data management strategies, incorporating industry standards and best practices, and leveraging expertise in managing large data repositories.

• Cloud Native Platform Expertise: Experience with Cloud native platforms such as AWS, Azure, Google, IBM Cloud, or Cloud Native data platforms like Snowflake, with the ability to leverage these platforms to create tailored data solutions.

• HADOOP Framework Knowledge: Deep understanding of the HADOOP Framework, Ecosystem, MapReduce, and Data on Containers (data in OpenShift), with the ability to apply this knowledge to design end-to-end Big Data Solutions.

• Unstructured Data Technology Understanding: Strong understanding of unstructured data technologies, annotation, and related data and analytics, with the ability to guide the architecture for data platform and cognitive components.

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