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Databricks Data Engineer - Manager - Consulting - Miami

Job in Grand Rapids, Kent County, Michigan, 49528, USA
Listing for: EY
Full Time position
Listed on 2026-01-15
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager, Data Analyst
Job Description & How to Apply Below

Databricks Data Engineer - Manager - Consulting - Miami

Join to apply for the Databricks Data Engineer - Manager - Consulting - Miami role at EY

Location

Anywhere in Country

Overview

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

Key Responsibilities
  • Understanding and analyzing business requirements to translate them into technical requirements.
  • Designing, building, and operating scalable data architecture and modeling solutions.
  • Staying up to date with the latest trends and emerging technologies to maintain a competitive edge.
  • Leading workstream delivery and ensuring quality in all processes.
  • Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services.
  • Implementing resource plans and budgets while managing engagement economics.
Skills and Attributes for Success
  • Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (e.g., AWS, Azure, GCP).
  • Oversee the architecture of complex cloud analytics solutions, ensuring alignment with business objectives and best practices.
  • Manage and mentor a team of data engineers, fostering a culture of innovation, collaboration, and continuous improvement.
  • Collaborate with clients to understand their analytics needs and deliver tailored solutions that drive business value.
  • Ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance.
  • Drive end-to-end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services.
  • Communicate effectively with stakeholders, including technical and non-technical audiences, to convey complex data concepts and project progress.
  • Manage client relationships and expectations, ensuring high levels of satisfaction and engagement.
  • Stay abreast of the latest trends and technologies in data engineering, cloud computing, and analytics.
  • Strong analytical and problem‑solving abilities.
  • Excellent communication skills, with the ability to convey complex information clearly.
  • Proven experience in managing and delivering projects effectively.
  • Ability to build and manage relationships with clients and stakeholders.
Qualifications
  • Bachelor’s degree in computer science, Engineering, or a related field required;
    Master’s degree preferred.
  • Typically, no less than 4‑6 years relevant experience in data engineering, with a focus on cloud data solutions and analytics.
  • Proven expertise in Databricks and experience with Spark for big data processing.
  • Strong background in data architecture and design, with experience in building complex cloud analytics solutions.
  • Experience in leading and managing teams, with a focus on mentoring and developing talent.
  • Strong programming skills in languages such as Python, Scala, or SQL.
  • Excellent problem‑solving skills and the ability to work independently and as part of a team.
  • Strong communication and interpersonal skills, with a focus on client management.
Required Expertise for Managerial Role
  • Strategic Leadership:
    Ability to align data engineering initiatives with organizational goals and drive strategic vision.
  • Project Management:
    Experience in managing multiple projects and teams, ensuring timely delivery and adherence to project scope.
  • Stakeholder Engagement:
    Proficiency in engaging with various stakeholders, including executives, to understand their needs and present solutions effectively.
  • Change Management:
    Skills in guiding clients through change processes related to data transformation and technology adoption.
  • Risk Management:

    Ability to identify potential risks in data projects and develop mitigation strategies.
  • Technical Leadership:
    Experience in leading technical discussions and making architectural decisions that impact project outcomes.
  • Documentation and Reporting:
    Proficiency in creating comprehensive documentation and reports to communicate project progress and outcomes to clients.
Large‑Scale Implementation…
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