Nasscomm
Data Engineer (W2 Only)
Job description
Title: Data Engineer|W2 Only
Locations: Cupertino, CA; New York City, NY; Austin, TX – (candidates within commuting distance) - 3 days a week client Office
Contract: 9+ Months
Job Description:
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 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.
Responsibilities
- 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
- 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
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 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
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