Databricks Data Engineer - Manager - Consulting

Databricks Data Engineer – Manager – Consulting – Location Open

Join EY as a Databricks Data Engineer – Manager – Consulting – Location Open to shape your future with confidence. This role leads a team in designing and implementing complex cloud analytics solutions focused on Databricks.

Location: Anywhere in Country

• 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.

• Lead the design and development of scalable data engineering solutions using Databricks on cloud platforms (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.

• 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 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.

• Strategic leadership: align data engineering initiatives with organizational goals and drive strategic vision.
• Project management: manage multiple projects and teams, ensuring timely delivery and adherence to project scope.
• Stakeholder engagement: engage with executives and other stakeholders, presenting solutions effectively.
• Change management: guide clients through data transformation and technology adoption.
• Risk management:
  
  identify potential risks and develop mitigation strategies.
• Technical leadership: lead technical discussions and make architectural decisions that impact project outcomes.
• Documentation and reporting: create comprehensive documentation and reports to communicate project progress and outcomes.

• Enterprise Data Lake Implementation: led the design and deployment of a cloud‑based data lake solution for a Fortune 500 retail client, integrating data from multiple sources to enable advanced analytics and reporting.
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