Database Engineer Contractor

Locations - Cupertino, CA; New York City, NY; Austin, TX
3 days a week, client Office

As a Database Engineer Contractor, you will design, develop, and optimize database systems to support data storage, retrieval, and analysis. Design and construct large relational databases to meet project requirements. Develop and maintain ETL processes to integrate new systems with existing data warehouse structures. Optimize database performance by refining system functionality and ensuring efficient data retrieval. Implement and enforce database security measures to protect data integrity and confidentiality. Perform regular data validation and quality checks to ensure database accuracy and reliability.

Primary Skill Required for the Role: Data Engineer

Level Required for Primary Skill: Advanced (6-9 years experience)

Additional Skills Requested for Role:

• ANSI SQL - Advanced (6-9 years experience) Required
• Python Data Engineering - Advanced (6-9 years experience) Required
• Pyspark - Advanced (6-9 years experience) Required
• GenAI Engineering - Entry Level (0-2 years experience) Preferred

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.

Key Responsibilities:

• 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.

Required Qualifications

• 6+ years of experience in data engineering for analytics or ML systems.
• Strong SQL proficiency.
• 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 Google Cloud Platform.
• 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.