Data Foundations Engineer

The Data Foundations Engineer designs and scales modern data architectures powering Wallet, Payments, and Commerce products. This role focuses on building high-performance data pipelines and enabling analytics and ML use cases, with strong fundamentals in data modeling and scalable systems.

• Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
• Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

Data Engineering & Architecture

• Design and implement scalable batch and near-real-time data pipelines.
• Develop ETL/ELT workflows optimized for performance and cost.
• Implement dimensional data models and standardize business metrics.
• Instrument APIs and user journeys to capture behavioral and transactional data.

Data Governance & Quality

• Ensure data integrity, governance, privacy, and compliance.
• Maintain reliability and availability of mission-critical systems.

The Team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

AI & Engineering - Industry Solutions teams works with the Customer group to bring a flexible capability and fluid capacity model to the delivery of small technology projects and enhancements.

Required

• 8+ years of experience in data engineering for analytics or ML systems.
• Strong SQL proficiency.
• 8+yrs experience in Python, Scala, or Java.
• Hands-on experience with Spark, Kafka, and Airflow (or similar).
• Strong understanding of data modeling and lakehouse architectures (e.g., Iceberg).
• Experience with AWS, Azure, or GCP.
• Comfortable participating in rotating on-call.
• Experience with Snowflake, Databricks, Trino, OLAP/NRT systems, Superset or Tableau.
• Familiarity with CI/CD, data observability, infrastructure-as-code.
• Exposure to MLOps and GenAI/RAG pipelines.
• Hands-on experience with LLMs (prompt engineering, fine-tuning, RAG).
• Experience in FinTech, Wallet, or Payments domain.
• Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
• Limited immigration sponsorship may be available
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
• Hybrid role - on-site Tue/Wed/Thu

For individuals assigned and/or hired to work in California, Deloitte is required by law to include a reasonable estimate of the compensation range for this role. This compensation range is specific to California and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $119,000 to $198,400.