Manager Data Engineer - AI Ready Data - EY wavespace AI & Data hub
Job description
About Us
At EY wavespace Madrid - AI & Data Hub, we are a diverse, multicultural team at the forefront of technological innovation, working with cutting-edge technologies like Gen AI, data analytics, robotics, etc. Our center is dedicated to exploring the future of AI and Data.
What We Offer
Join our Data & AI Hub, where you will have the chance to work in a vibrant and collaborative environment. You will engage directly with building AI ready Data solutions, where you'll leverage cutting-edge technologies to drive innovative data solutions and transform business insights. Our team supports your growth and development, providing access to the latest tools and resources.
As a Data Engineer at EY wavespace, you will embark on a journey to take a data engineer role to the next level. You will meet with opportunities to engage with cutting-edge technologies and innovative architectures that drive AI and data-driven solutions. Collaborating closely with the AI domain at our AI & Data hub, you will confront complex challenges that stretch the limits of what is possible in data engineering, ensuring that your work is not only technically stimulating but also impactful in shaping the future of our clients' businesses.
Key Responsibilities:
- Lead and mentor a high-performing data engineering team, fostering a culture of collaboration, innovation, and continuous improvement,
- Engage with internal and external clients to assess their needs, develop tailored solutions, and present strategic proposals that align with their business objectives.
- Oversee the design and implementation of scalable data pipelines using Databricks (PySpark, Delta Lake), Snowflake, and/or Microsoft Fabric.
- Manage data integration processes.
- Identify and enforce best practices for data quality, observability, lineage, and metadata management.
- Drive data modernization initiatives, ensuring that data architectures are AI-ready and capable of supporting advanced analytics.
- Supervise data profiling and cleansing activities to maintain high data quality and integrity across all data systems.
- Lead the implementation process of streaming systems to enable real-time data processing and analytics.
Qualifications:
- Bachelor's or master's degree in computer science, Information Technology, Data Science, or a relevant field.
- 5 - 7 years of relevant experience.
- Proven track record in managerial role within data engineering, preferably in consulting or financial services.
- Strong hands-on expertise in Databricks, Snowflake, and Azure, with a focus on delivering projects in MS/Databricks environments.
- Expertise in data processing, cloud data architecture, and data warehouse principles.
- Experience in Data Governance, Unity Catalog, and/or MS Purview, with the ability to guide teams in implementing best practices.
- Excellent programming skills in Python and SQL.
- Strong communication and interpersonal skills, with a demonstrated ability to engage clients, solve complex problems, and drive team success.
- Proficiency in English and Spanish, both written and spoken.
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