EY
Databricks Data Engineer - Manager - Consulting - Miami
Location: Anywhere in Country 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 build a better working world. We are looking for a dynamic and experienced Manager of Data Engineering to lead our team in designing and implementing complex cloud analytics solutions with a strong focus on Databricks. The ideal candidate will possess deep technical expertise in data architecture, cloud technologies, and analytics, along with exceptional leadership and client management skills. Opportunity
In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions. 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. Key Responsibilities
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 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 ability to work independently and as part of a team. Strong communication and interpersonal skills, with a focus on client management. Managerial Role Expertise
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 scope. Stakeholder Engagement: Engage executives and other stakeholders to understand their needs and present solutions effectively. Change Management: Guide clients through data transformation and technology adoption processes. Risk Management: Identify potential risks in data projects 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 to clients. Large‑Scale Implementation Programs
Enterprise Data Lake Implementation: Designed and deployed a cloud‑based data lake solution for a Fortune 500 retail client, integrating data from multiple sources to enable advanced analytics and reporting capabilities. Real‑Time Analytics Platform: Managed the development of a real‑time analytics platform using Databricks for a financial services organization, enabling real‑time fraud detection and risk assessment through streaming data ingestion and processing. Data Warehouse Modernization: Oversaw modernization of a legacy data warehouse to a cloud‑native architecture for a healthcare provider, implementing ETL processes with Databricks and improving data accessibility for analytics and reporting. Ideal Additional Experience
Experience with advanced data analytics tools and techniques. Familiarity with machine learning concepts and applications. Knowledge of industry trends and best practices in data engineering. Familiarity with cloud platforms (AWS, Azure, GCP) and their data services. Knowledge of data governance and compliance standards. Experience with machine learning frameworks and tools. What We Look For
We seek individuals who are not only technically proficient but also possess the qualities of top performers, including a strong sense of collaboration, adaptability, and a passion for continuous learning. If you are driven by results and have a desire to make a meaningful impact, we want to hear from you. What We Offer You
At EY, we’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment and fuel your extraordinary talents in a diverse and inclusive culture of globally connected teams. Competitive compensation: $125,500‑$230,200 base salary in the US (location adjustments apply). Total Rewards include medical and dental coverage, pension and 401(k) plans, and paid time off. Hybrid working model: 40‑60% in‑person work for external client‑serving roles. Flexible vacation policy: Choose how much vacation you need based on your personal circumstances. Additional time off for holidays, personal/family care, and other leaves of absence. EY accepts applications for this position on an ongoing basis. EY is an equal‑employment‑opportunity employer. We provide reasonable accommodations for qualified individuals with disabilities. For assistance, call 1‑800‑EY‑HELP3 or email ssc.customersupport@ey.com.
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Location: Anywhere in Country 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 build a better working world. We are looking for a dynamic and experienced Manager of Data Engineering to lead our team in designing and implementing complex cloud analytics solutions with a strong focus on Databricks. The ideal candidate will possess deep technical expertise in data architecture, cloud technologies, and analytics, along with exceptional leadership and client management skills. Opportunity
In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that business requirements are translated into effective technical solutions. 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. Key Responsibilities
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 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 ability to work independently and as part of a team. Strong communication and interpersonal skills, with a focus on client management. Managerial Role Expertise
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 scope. Stakeholder Engagement: Engage executives and other stakeholders to understand their needs and present solutions effectively. Change Management: Guide clients through data transformation and technology adoption processes. Risk Management: Identify potential risks in data projects 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 to clients. Large‑Scale Implementation Programs
Enterprise Data Lake Implementation: Designed and deployed a cloud‑based data lake solution for a Fortune 500 retail client, integrating data from multiple sources to enable advanced analytics and reporting capabilities. Real‑Time Analytics Platform: Managed the development of a real‑time analytics platform using Databricks for a financial services organization, enabling real‑time fraud detection and risk assessment through streaming data ingestion and processing. Data Warehouse Modernization: Oversaw modernization of a legacy data warehouse to a cloud‑native architecture for a healthcare provider, implementing ETL processes with Databricks and improving data accessibility for analytics and reporting. Ideal Additional Experience
Experience with advanced data analytics tools and techniques. Familiarity with machine learning concepts and applications. Knowledge of industry trends and best practices in data engineering. Familiarity with cloud platforms (AWS, Azure, GCP) and their data services. Knowledge of data governance and compliance standards. Experience with machine learning frameworks and tools. What We Look For
We seek individuals who are not only technically proficient but also possess the qualities of top performers, including a strong sense of collaboration, adaptability, and a passion for continuous learning. If you are driven by results and have a desire to make a meaningful impact, we want to hear from you. What We Offer You
At EY, we’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment and fuel your extraordinary talents in a diverse and inclusive culture of globally connected teams. Competitive compensation: $125,500‑$230,200 base salary in the US (location adjustments apply). Total Rewards include medical and dental coverage, pension and 401(k) plans, and paid time off. Hybrid working model: 40‑60% in‑person work for external client‑serving roles. Flexible vacation policy: Choose how much vacation you need based on your personal circumstances. Additional time off for holidays, personal/family care, and other leaves of absence. EY accepts applications for this position on an ongoing basis. EY is an equal‑employment‑opportunity employer. We provide reasonable accommodations for qualified individuals with disabilities. For assistance, call 1‑800‑EY‑HELP3 or email ssc.customersupport@ey.com.
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