Databricks Data Engineering Manager

Location: Anywhere in Country Technology – Data and Decision Science – Data Engineering – Manager 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. The 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 As a Data Engineering Manager, you will play a crucial role in managing and delivering complex technical initiatives. Your time will be spent across various responsibilities, including: 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. Travel may be required regularly based on client needs. 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. To qualify for the role, you must have: Bachelor’s degree in computer science, engineering, or a related field required; master’s degree preferred. No less than 4–6 years of 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: 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 various stakeholders, including executives, to understand needs and present solutions effectively. Change management: guide clients through change processes related to data transformation and technology adoption. 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: led 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. Real‑Time Analytics Platform: managed development of a real‑time analytics platform using Databricks for a financial services organization, enabling fraud detection and risk assessment through streaming data ingestion. 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. Ideally, you’ll also have 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. 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 Comprehensive compensation and benefits package, including medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Base salary range for the U.S. is $125,500 to $230,200, with higher ranges for select metro areas. Individual salaries are determined by education, experience, skills, and geography. Hybrid work model: most external, client‑serving roles will work together in person 40–60% of the time over the course of an engagement, project or year. Flexible vacation policy: determine your own vacation time based on personal circumstances, with additional time off for EY Paid Holidays, seasonal breaks, personal/family care, and other leaves of absence. EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. EY is committed to providing reasonable accommodation to qualified individuals with disabilities, including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate–related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry, which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at View email address on click.appcast.io. #J-18808-Ljbffr EY