Data Engineering

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Company Overview

A leading financial technology organization is focused on making financial services more accessible and empowering individuals to participate in the financial system. The organization combines technology, data, and innovative financial products to address complex challenges and improve the customer experience.

The Data Engineering team develops and maintains foundational datasets that support decision-making across the organization. The team builds reliable and scalable data systems for product analytics, growth strategy, financial reporting, experimentation, and machine learning. Data engineers collaborate closely with Product, Engineering, Data Science, and Finance teams to ensure accurate, well-modeled, and accessible data.

The organization is seeking a Senior Software Engineer, Data Engineering to design, build, and evolve core datasets that track product performance and company-wide metrics. The role will involve developing scalable data pipelines that ingest application events and database snapshots into a data lake while maintaining high standards for data quality and reliability.

The successful candidate will collaborate with application engineering teams to improve data generation patterns and work with analytics teams to develop intuitive and well-documented data models. This position provides an opportunity to shape the technical foundation that enables data-informed decisions across the organization.

The role is based in the Menlo Park, California office, with in-person attendance expected at least three days per week. The organization values in-person collaboration as a way to accelerate progress, encourage innovation, and strengthen team connections.

Key Responsibilities

• Define and build key datasets supporting products and business functions across the organization.
• Lead the evolution of datasets as business requirements and use cases expand.
• Build scalable data pipelines using Python, Spark, and Airflow to move data from multiple applications into the data lake.
• Partner with upstream engineering teams to improve data generation patterns.
• Collaborate with data consumers to understand data consumption patterns and develop intuitive data models.
• Contribute ideas and technical solutions to shared data engineering tools and standards.
• Establish and promote data engineering best practices across the organization.
• Help maintain reliable, scalable, and high-quality data infrastructure.
• Collaborate across Product, Engineering, Data Science, Analytics, and Finance teams to support data-driven decision-making.

Required Qualifications

• 5+ years of professional experience building end-to-end data pipelines.
• Hands-on software engineering experience with the ability to write production-level Python code for user-facing applications, services, or systems.
• Expert-level experience building and maintaining large-scale data pipelines using open-source frameworks such as Spark or Flink.
• Strong SQL skills, including experience with technologies such as Presto and Spark SQL.
• Experience solving technical challenges across the data stack, including data infrastructure, analytics, and visualization platforms.
• Strong collaboration and communication skills.
• Ability to translate complex data into actionable insights and practical solutions.
• Experience designing reliable, scalable, and well-documented data systems.

What the Organization Offers

• Challenging, high-impact work designed to support professional and career growth.
• Performance-driven compensation, including bonuses, equity ownership, and 401(k) matching.
• Comprehensive benefits designed to support employees and their families.
• Employer-supported health insurance and dependent coverage.
• Flexible lifestyle benefits supporting wellness, learning, and other personal needs.
• Employer-paid life and disability insurance.
• Fertility and mental health benefits.
• Paid time off, company holidays, sick time, parental leave, and additional time away to recharge.
• An exceptional office environment with catered meals, events, and comfortable workspaces.

Disclaimer

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