EY - GDS Consulting - AI and DATA - Data Engineer Lead - Manager

Rank Manager

Objectives and Purpose

Lead Data Engineer

The Lead Data Engineer will:

• Implement data processes for the data warehouse and internal systems
• Lead a team of Junior and Senior Data Engineers in executing data processes and providing quality, timely data management
• Manage data architecture, design ETL processes
• Clean, aggregate and organize data from disparate sources and transfer it to data warehouses
• Lead development, testing and maintenance of data pipelines and platforms, to enable data quality to be utilized within business dashboards and tools
• Support team members and direct reports in refining and validating data sets
• Create, maintain, and support the data platform and infrastructure that enables the analytics front-end; this includes the testing, maintenance, construction, and development of architectures such as high-volume, large-scale data processing and databases with proper verification and validation processes

Your Key Responsibilities

Data Engineering

• Lead the design, development, optimization, and maintenance of data architecture and pipelines adhering to ETL principles and business goals
• Develop and maintain scalable data pipelines, build out new integrations using

  AWS native technologies and Databricks

• Define data requirements, gather and mine large scale structured and unstructured data, and validate data in the Big Data Environment
• Lead ad hoc data analysis, support standardization/customization and develop mechanisms to ingest, analyze, validate, normalize, and clean data
• Write unit/integration/performance test scripts and troubleshoot data-related issues
• Implement processes and systems to drive

  data reconciliation and monitor data quality

  , ensuring accurate and available production data
• Lead evaluation and deployment of emerging tools for analytic data engineering
• Develop communication and education plans for data engineering capabilities
• Solve complex data problems to deliver business insights
• Partner with Business Analysts and Enterprise Architects for strategic technical architecture
• Coordinate with Data Scientists, visualization developers, and other data consumers

Relationship Building and Collaboration

• Collaborate across technical and business teams to develop scalable analytics and machine learning solutions
• Support Data Scientists in data sourcing/preparation for visualization and insights
• Mentor other data and analytics professionals on best practices
• Foster a collaborative culture of reusable design and scalable solutions

Skills and Attributes for Success

Technical/Functional Expertise

• Advanced experience in

  Big Data, data integration, data modeling, AWS, cloud technologies

• Business acumen, preferably in

  Pharmaceutical, Healthcare, or Life Sciences

• Strong in

  SQL, data transformations, metadata management

• Familiar with

  Agile methodologies

Leadership

• Mentor Senior and Junior Engineers
• Strategic thinker aligned with long-term business goals
• Promote psychological safety and team collaboration

Decision-making and Autonomy

• Promote

  data-driven decisions

  over manual decisions
• Strong problem-solving and critical thinking skills

Interaction

• Proven ability to develop trust-based relationships with stakeholders
• Work across IT functions and vendors

Innovation

• Advocate for

  disruptive technologies

  and

  advanced data solutions

• Lead R&D efforts in

  data engineering

• Embrace a

  growth mindset

  and

  continuous learning

Complexity

• Culturally sensitive and effective across global teams
• Skilled in large-team coordination and problem solving

To Qualify for the Role, You Must Have the Following:

Essential Skillsets

• Bachelor's in

  Engineering, Computer Science, Data Science

  , or related

• 9+ years

  in software development, data engineering, ETL, and reporting
• Expert in dimensional data modeling, ETL pipelines
• Hands-on with

  data mesh, data fabric, data product design

• Knowledge of structured/unstructured data frameworks
• Proven complex data solutions design and implementation

Technical Experience With:

• Python, PySpark

• Kubernetes, AWS (Lambda, S3, DMS, Step Functions, Event Bridge, CloudWatch, RDS)

• Databricks, IICS/DMS, GitHub, SQL

• Lakehouse/Data Lake

  architecture

• CI/CD using GitHub Actions

• Optimizing Python/Spark scripts and

  AWS/Databricks cloud costs

• Strong communication and organizational skills

Desired Skillsets

• Master's degree

  in a relevant field

• Global working environment

  experience

Travel Requirements

• Access to transportation for meetings
• Willingness to travel regionally and globally

About EY

EY | Building a better working world

• EY exists to create long-term value for clients, people, and society
• Operating in over 150 countries
• Offering services in

  assurance, consulting, law, strategy, tax, and transactions

• Driving transformation with

  data, technology, and diversity