Databricks Data Engineer - Manager - Consulting

Databricks Data Engineer - Manager - Consulting - Location Open

Join EY as a Manager of Data Engineering to lead the design and implementation of complex cloud analytics solutions with a strong focus on Databricks. In this role you will partner with data and analytics professionals, management, and stakeholders to translate business requirements into effective technical solutions.

• Understand and analyze business requirements and translate them into technical specifications.
• Design, build, and operate scalable data architecture and modeling solutions.
• Stay current with emerging technologies and industry trends to maintain a competitive edge.
• Lead workstream delivery and ensure quality throughout all processes.
• Engage with clients daily, participate in working sessions, and identify opportunities for additional services.
• Implement resource plans and budgets while managing engagement economics.
• Travel as required based on client needs.

• Lead design and development of scalable data engineering solutions using Databricks on AWS, Azure, or GCP.
• Oversee complex cloud analytics solution architecture, aligning with business objectives and best practices.
• Manage and mentor a team of data engineers, fostering innovation and continuous improvement.
• Collaborate with clients to understand analytics needs and deliver tailored solutions that drive business value.
• Ensure data quality, integrity, and security throughout the data lifecycle, implementing data governance best practices.
• Drive end‑to‑end data pipeline development, including ingestion, transformation, and storage using Databricks and related cloud services.
• Communicate effectively with technical and non‑technical stakeholders, conveying complex data concepts and project progress.
• Manage client relationships and expectations, ensuring high satisfaction and engagement.
• Stay abreast of 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.

• Bachelor’s degree in Computer Science, Engineering, or related field required;
  Master’s degree preferred.
• Typically 4‑6 years of experience in data engineering, focusing on cloud data solutions and analytics.
• Proven expertise in Databricks and Spark for big data processing.
• Strong background in data architecture and design, building complex cloud analytics solutions.
• Experience leading and managing teams, focusing on mentoring and talent development.
• Strong programming skills in Python, Scala, or SQL.
• Excellent problem‑solving skills and ability to work independently and as part of a team.
• Strong communication and interpersonal skills, with a focus on client management.

• Strategic leadership aligning data initiatives with organizational goals.
• Project management experience ensuring timely delivery and adherence to scope.
• Stakeholder engagement, including executives, to understand needs and present solutions.
• Change management, guiding clients through data transformation and technology adoption.
• Risk management, identifying potential risks and developing mitigation strategies.
• Technical leadership in architectural decisions impacting project outcomes.
• Documentation and reporting of project progress and outcomes.

• Enterprise Data Lake Implementation for a Fortune 500 retail client, integrating data from ERPs, POS, and e‑commerce platforms.
• Real‑Time Analytics Platform for a financial services organization, enabling fraud detection via streaming data ingestion.
• Data Warehouse Modernization for a healthcare provider, transitioning from legacy to cloud‑native architecture with Databricks ETL.

• Advanced data analytics tools and techniques experience.
• Machine learning concepts and applications familiarity.
• Knowledge of industry trends and best practices in data engineering.
• Experience with cloud platforms (AWS,…