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Management Consultant - Data Engineer

IBM

Remote · USJobSeen 2 days agoSeen in employer's feed 2 days ago

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At a glance

Compensation
No compensation found
Location
Remote · US
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Data And AI Certification

Job overview

The Data Engineer will build and enhance the Databricks platform for client Data and AI use cases, implementing solutions that meet client needs. The role includes improving platform performance and scalability and leading solution delivery in collaboration with clients and stakeholders. The position can be performed from anywhere in the US.

Skills & qualifications

RequiredNice to have

Skills

DatabricksData EngineeringData ProcessingData Storage and RetrievalData PipelinesCloud ComputingCloud Platform MigrationCloud DeploymentCloud ManagementSolution DeliveryCloud MigrationData WarehousingETLData GovernanceAI Solution DevelopmentNatural Language ProcessingMachine LearningDeep Learning

Qualifications

Data and AI Certification

Full job description

Introduction

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.

Your role and responsibilities

As a Data Engineer specializing in Data Platforms-Databricks, you will play a critical role in building and enhancing the Databricks platform for client's Data and AI use cases. This position is responsible for implementing Data and AI use cases on the Databricks platform.

Your primary responsibilities will include:

  • Implement Data and AI Use Cases: Design, develop, and deploy data and AI solutions on the Databricks platform to meet client needs, driving business value through data-driven insights.

  • Enhance Databricks Platform: Collaborate with stakeholders to identify areas for improvement and implement enhancements to the Databricks platform, ensuring optimal performance and scalability.

  • Drive Solution Delivery: Lead the delivery of data and AI solutions, working closely with clients to understand their requirements and ensure successful project outcomes.

*This job can be performed from anywhere in the US.

Required technical and professional expertise

  • Deep Expertise in Databricks: Proven experience with designing, developing, and deploying data and AI solutions on the Databricks platform, with a strong understanding of its architecture and capabilities.

  • Experience with Data Engineering: Skilled in data engineering principles, including data processing, storage, and retrieval, with the ability to apply this knowledge to build scalable and efficient data pipelines.

  • Cloud Computing Knowledge: Experience with cloud-based technologies and infrastructure, including migration, deployment, and management of cloud-based data platforms.

  • Certification in Data and AI: Possession of relevant certifications in data engineering, data science, or AI, demonstrating expertise in implementing data and AI use cases on cloud-based platforms.

  • Experience with Solution Delivery: Proven track record of leading the delivery of data and AI solutions, working closely with clients to understand their requirements and ensure successful project outcomes.

Preferred technical and professional experience

  • Cloud Migration Expertise: Experience with migrating data platforms to cloud-based infrastructure, including planning, execution, and post-migration optimization. Ability to assess existing infrastructure and develop strategies for seamless migration to cloud-based environments.

  • Advanced Data Engineering: Deep understanding of data engineering principles, including data warehousing, ETL, and data governance. Ability to design and implement scalable and efficient data pipelines, leveraging expertise in data processing, storage, and retrieval.

  • AI Solution Development: Experience with developing and deploying AI solutions on cloud-based platforms, including natural language processing, machine learning, and deep learning. Ability to collaborate with stakeholders to identify business opportunities and develop AI-powered solutions to drive business value.

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

How this job compares

Set against the 5,633 open Data Engineer jobs on Olive Jobs, counted November 2, 2026.

Pay
  • This postingNot listed
  • New York median$150–213K/yr360 salary ranges
  • US median$61–75/hr264 hourly ranges
Openings
Olive Jobs lists 471 open Data Engineer jobs in New York and 5,633 across the US. 9% of them nationwide are listed as remote or flexible.
Hiring the most in New York
Experience
Data Engineer postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 6 years (4,882 postings).
Education
2,157 of the 5,633 open Data Engineer jobs (38%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 2, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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