Overview
Join to apply for the Databricks Data Engineer - Manager - Consulting - Location Open role at EY
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 to build a better working world.
What you will do
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.
- Understand and analyze business requirements to translate them into technical requirements.
- Design, build, and operate scalable data architecture and modeling solutions.
- Stay up to date with the latest trends and emerging technologies to maintain a competitive edge.
Key Responsibilities
- Lead workstream delivery and ensure quality in 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 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 data governance best practices.
- Drive end-to-end data pipeline development, including data ingestion, transformation, and storage, leveraging Databricks and other cloud services.
- Communicate effectively with stakeholders 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; proven experience in managing and delivering projects.
Qualifications
- Bachelor’s degree in computer science, Engineering, or a related field required; Master’s degree preferred.
- Typically, 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 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 scope.
- Stakeholder Engagement: Engage with executives and other stakeholders to understand needs and present solutions.
- Change Management: Guide clients through data transformation and technology adoption.
- Risk Management: Identify risks and develop mitigation strategies.
- Technical Leadership: Lead technical discussions and make architectural decisions that impact outcomes.
- Documentation and Reporting: Create comprehensive documentation and reports for clients.
Large-scale implementation programs
- Enterprise Data Lake Implementation: Cloud-based data lake for a Fortune 500 retail client, integrating data from multiple sources to enable analytics.
- Real-Time Analytics Platform: Real-time analytics platform using Databricks for a financial services organization, enabling fraud detection and risk assessment.
- Data Warehouse Modernization: Cloud-native architecture modernization for a healthcare provider, with ETL via Databricks.
Additional qualifications (ideally)
- 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.
- 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 offer
EY offers a comprehensive compensation and benefits package with salary ranges and a Total Rewards program. The exact base salary varies by geographic location and is determined by education, experience, and other factors. EY supports a hybrid work model and flexible vacation policies, with leave options to support well-being.
We are committed to equal employment opportunities and provide reasonable accommodation to qualified individuals with disabilities. For accommodations or inquiries, contact EY’s Talent Shared Services Team.
EY | Building a better working world
Legal and accessibility
We focus on high ethical standards and integrity. EY is an equal opportunity employer and does not discriminate on any legally protected basis. EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you need assistance applying online or an accommodation during the application process, please contact EY’s Talent Shared Services Team.
Seniority level
- Mid-Senior level
Employment type
- Full-time
Job function
- Information Technology
- Industries: Professional Services