채용
About us:
- At EY wavespace
- AI & Data CoE, we are a diverse, multicultural team at the forefront of technological innovation, working with cutting-edge technologies like Gen AI, AI ready Data, robotics, etc. Our center is dedicated to exploring the future of AI and Data.
What We Offer:
Join our AI & Data CoE, where you will play a key role in shaping and delivering complex data initiatives within a highly collaborative and forward‑thinking environment. You will work hands‑on with advanced data engineering practices and cutting‑edge technologies, driving scalable solutions that enable strategic insights across the business. In this role, you will influence architecture decisions, mentor team members, and contribute to the evolution of our data capabilities.
Key Responsibilities:
Act as the technical lead and trusted advisor for data platform strategies, solution design and guiding clients through architectural decisions.
Guide teams in data modeling, database management, ETL/ELT, and integration patterns.
Oversee data engineering practices including data modeling, database management, ETL/ELT pipelines, data storage, and realtime/batch integrations.
Partner with value proposition leads and consulting teams to support presales cycles, including discovery sessions, solution shaping, estimations, and RFP responses.
Build strong relationships with clients as a trusted advisor, ensuring alignment between business objectives and technical solutions.
Ensure quality control of deliverables and offerings, implementing best practices and standards.
Mentor data engineers and consultants, fostering a culture of learning and excellence.
Promote knowledge sharing and cross-team collaboration.
Collaborate closely with business stakeholders, product teams and peers to ensure cohesive and successful project outcomes.
Evaluate emerging tools, platforms, and methodologies to enhance the data and analytics offerings.
Contribute to internal assets such as reference architectures, accelerators, reusable components, and bestpractice frameworks.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
Proven experience designing and delivering data solution architectures, ideally within cloud and modern data platform environments.
Strong background in data architecture frameworks, data modeling, data governance, and best practices for scalable data platforms.
Comfortable in client-facing roles, with strong communication and stakeholder engagement skills.
Experience in presales, including requirements discovery, solution definition, cost estimation, and supporting RFP/RFI responses.
Demonstrated ability to build proposals, lead project delivery, and manage resources (budgeting, team planning, timelines).
Prior experience in consulting, professional services, or financial services is highly valued.
Fluency in English and Spanish, both written and spoken.
Hands-on expertise with modern data technologies such as Azure Data Services, Databricks, and Snowflake.
Our commitment to diversity & inclusion
We are genuinely passionate about inclusion and we support individuals of all groups; we do not discriminate on the basis of race, religion, gender, sexual orientation, or disability status.
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EY 소개

EY
PublicEY, previously known as Ernst & Young, is a British multinational professional services network based in London, United Kingdom. Along with Deloitte, KPMG and PwC, it is one of the Big Four professional services firms.
10,001+
직원 수
London
본사 위치
리뷰
3.4
10개 리뷰
워라밸
2.3
보상
3.7
문화
4.1
커리어
3.8
경영진
3.2
65%
친구에게 추천
장점
Good learning opportunities and career advancement
Supportive culture and kind people
Professional environment and good benefits
단점
Long working hours and poor work-life balance
Hectic and taxing work environment
Limited support for interns and technical growth
연봉 정보
31,254개 데이터
Mid/L4
Mid/L4 · Operations Research Analyst
1,738개 리포트
$142,571
총 연봉
기본급
$136,899
주식
-
보너스
$5,673
$100,128
$203,912
면접 경험
7개 면접
난이도
3.0
/ 5
소요 기간
14-28주
합격률
57%
면접 과정
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Technical/Case Interview
5
Partner/Director Interview
6
Offer
자주 나오는 질문
Behavioral/STAR
Case Study
Technical Knowledge
Past Experience
Culture Fit
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