Job Description

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Technical Data Product Engineer

Experience:3–7 Years

If you’re excited about building data systems that don’t just move data—but power products and decisions—this role is for you.

About the Role

We are building the next generation of data platforms and data products that power intelligent decision-making, customer experiences, and AI-driven innovation at scale.

As a Technical Product Data Engineer, you will operate at the intersection of data engineering, platform architecture, and product thinking. You will own the design and delivery of scalable, reliable, and high-impact data systems—transforming raw data into trusted, accessible, and actionable data products.

This is a high-ownership role for engineers who want to go beyond pipelines and shape how data is produced, consumed, and leveraged across the organization.

What You’ll Do

• Build Data Products, Not Just Pipelines
• Design and develop end-to-end data products that serve analytics, operational, and AI use cases
• Define data SLAs, quality benchmarks, and usability standards

Engineer at Scale

• Build and optimize high-performance data pipelines (batch & real-time)
• Architect cloud-native data platforms for scalability, reliability, and cost efficiency

Drive Data Excellence

• Ensure data quality, lineage, governance, and discoverability
• Implement robust monitoring, alerting, and anomaly detection systems

Partner with Stakeholders

• Collaborate with product, analytics, and business teams to translate requirements into data solutions
• Enable self-service data access through well-modeled datasets and APIs

Influence the Future Architecture

• Contribute to modern data architecture strategy (lakehouse, event-driven systems)
• Continuously improve systems for performance, reliability, and developer experience

What You Bring

Must-Have Skills

• Strong programming in Python and SQL
• Hands-on experience with distributed data processing (Spark or equivalent)
• Experience building pipelines using Airflow (or similar orchestration tools)
• Solid understanding of data modeling, warehousing, and data lakes/lakehouse architectures
• Experience with cloud platforms (AWS / Azure / GCP)
• Strong foundation in data quality, observability, and reliability engineering

Good-to-Have

• Real-time streaming experience (Kafka, Kinesis, etc.)
• Experience with Snowflake, Databricks, or modern data platforms
• Building or consuming REST APIs for data services
• Exposure to ML/AI pipelines or feature engineering workflows
• Familiarity with DevOps practices (CI/CD, Git, Jenkins, Azure DevOps)
• Basic frontend exposure (React/Angular) for data tooling

Qualifications

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field
• 3+ years of experience in data engineering or data platform development

Additional

• Certifications in cloud or data engineering
• Experience with data governance, security, and compliance standards

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.