Note: The job is a remote job and is open to candidates in USA. EY is a globally connected professional services organization focused on building a better working world through assurance, consulting, tax, strategy, and transactions. EY is seeking a Senior Data Engineer for its Advanced Forward Engineering delivery pods to build governed, production-ready data integrations that support AI systems in regulated client environments. The role designs and operates data pipelines, partners with software engineers and stakeholders, and resolves data quality and integration issues across deployment environments.
Responsibilities
- Serve as the data owner within an AFE delivery pod, ensuring data readiness does not block or delay delivery outcomes
- Design and implement data ingestion, transformation, and access patterns that integrate AI systems with client and legacy data sources
- Ensure data pipelines comply with governance, security, lineage, and access control requirements mandated by regulated environments
- Implement data interfaces and contracts that satisfy DevOps Specification (DS) data requirements for supported deployment templates
- Partner closely with Forward Deployed Software Engineer roles to enable AI workflows, retrieval, and analytics that are reliable in production
- Diagnose and resolve data quality, schema drift, and integration issues encountered in real deployment scenarios
- Contribute reusable data patterns and implementation learnings back to the AFE integration core to improve repeatability across pods
- Support validation, testing, and deployment activities to ensure data flows behave correctly and consistently across environments (dev, test, pre-prod, prod)
Skills
- • Deep expertise with industry standard database and data management systems (Postgres, Oracle, Databricks, SnowFlake, BigQuery, RedShift, Azure Data Factory, Kafka, Flink, Spark)
- • Strong foundation in data engineering concepts applied to real production systems
- • Capable of working effectively with imperfect, heterogeneous, and legacy data environments
- • Experience in balancing delivery speed with data governance and compliance requirements
- • Pragmatic problem‑solver who can operate with ambiguity and incomplete information
- • Clear communicator able to explain data constraints and tradeoffs to engineers and stakeholders
- • Bias toward building durable, well‑understood data interfaces rather than one‑off solutions
- • Curiosity and flexibility when working with evolving AI and data use cases
- • Bachelor's or Master's degree in Computer Science or related technical field
- • 5+ years of experience in data engineering, data integration, or analytics engineering roles
- • Hands‑on experience building and operating data pipelines in cloud or hybrid environments
- • Experience integrating with relational databases, data warehouses, data lakes, or enterprise systems
- • Familiarity with data modeling, transformation frameworks, and API‑based data access
- • Experience working under data governance, security, or compliance constraints
- • Ability to collaborate closely with application engineers and operate in delivery‑focused teams
- • Experience supporting AI, ML, or analytics‑driven applications in production
- • Familiarity with retrieval‑based systems (e.g., search, embeddings, feature stores)
- • Exposure to regulated industry data environments (financial services, tax, healthcare)
- • Experience with hybrid or on‑prem data integration scenarios
- • Background in forward‑deployed, consulting, or customer‑facing engineering roles
Benefits
- Medical and dental coverage
- Pension and 401(k) plans
- A wide range of paid time off options
- Team-led and leader-enabled hybrid model
- Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances.
- Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
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