Data Foundations Engineer

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. Pay Range: $45-$50/hour We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

SKILLS AND REQUIREMENTS

Strong SQL proficiency. Experience in Scala. Experience in Python 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. #J-18808-Ljbffr Insight Global