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Early Warning® · 6 hours ago

Sr. Staff Engineer - Data Engineering

San Francisco, CA

Full-time

Hybrid

Senior Level, Lead/Staff

$175K/yr - $225K/yr

12+ years exp

Early Warning is a trusted name in payments, partnering with thousands of institutions to enhance financial services. The Sr. Staff Engineer - Data Engineering role involves leading the development and long-term health of large-scale data engineering solutions while driving data platform and architecture decisions across teams.

Financial ServicesFraud DetectionPaymentsRisk Management

No H1B

Responsibilities

Partner with software engineering, product, and architecture teams to shape data engineering approaches and share knowledge across the organization

Own the data and technical strategy for broad or complex requirements, taking forward-looking approaches that extend beyond a single team and address large, open-ended problems

Define and influence department-wide data architecture, design patterns, and code standards

Review and validate the effectiveness, quality, and scalability of code produced by multiple teams

Be accountable for resolving technical conflicts within and across teams

Drive technical architecture, design, prototyping, and implementation in support of product needs and overall technology and data strategy

Represent engineering in cross-functional forums; present clear, well-reasoned technical arguments and influence alignment and outcomes

Collaborate with product managers, designers, and engineering groups to conceptualize and build new data-driven features

Actively own data platforms, pipelines, or systems and define their long-term health, while improving the reliability and scalability of surrounding systems

Assist Support and Operations teams in identifying and resolving production issues

Develop and implement tests and validation mechanisms to ensure data quality, performance, and scalability

Mentor and develop other engineers and serve as a technical leader on cross-functional initiatives

Proactively identify opportunities to improve engineering standards, tooling, and processes

Support the company’s commitment to risk management and the protection of the integrity, availability, and confidentiality of systems and data

Qualification

Data engineeringCloud infrastructureETL developmentData architectureMachine learningPythonDockerAgile methodologiesCI/CDBig data platformsMentoringCollaborationProblem-solvingCommunication

Required

Education and/or experience typically obtained through a Bachelor's degree in Computer Science or a related technical field

Twelve or more years of relevant professional experience

Nine or more years of experience designing and developing complex data-intensive systems, including data platforms, distributed systems, SaaS, and cloud-based solutions

Two or more years of experience building end-to-end data management platforms, including data modeling, data governance, BI/reporting, and ML lifecycle support

Five or more years of experience with ETL or data pipeline development (e.g., Ab Initio, Talend, Informatica, or comparable tools) and BI/reporting solutions (e.g., Tableau, Business Objects, Grafana, or similar tools)

Experience working with advanced analytics or ML workloads using tools such as Python, PySpark, or Spark

Hands-on experience with Docker and containerized workloads

Experience designing and developing scalable, highly available systems

Experience with event-driven architectures and messaging frameworks (e.g., Pub/Sub, Kafka, RabbitMQ)

Hands-on experience with cloud infrastructure platforms (GCP, AWS, Azure, or equivalent)

Strong knowledge of mature engineering practices, including CI/CD, automated testing, secure coding, SDLC best practices, Agile methodologies, and DevOps practices

Demonstrated experience delivering business-critical, production-grade systems

Proven ability to influence and collaborate across multiple teams and departments

Background and drug screen

Preferred

Master's or PhD in Computer Science or a related field

Understanding of ML frameworks or platforms such as TensorFlow, SageMaker, or Scikit-learn

Experience with big data platforms and object storage (e.g., Cloudera, S3)

Experience with relational and enterprise database platforms (e.g., Oracle, SQL Server)

Strong programming experience in Python and PySpark; familiarity with R is a plus

Knowledge of Aerospike, Scality S3, or Elasticsearch

Experience with monitoring and alerting systems (e.g., AppDynamics)

Knowledge of ACH/EFT and real-time payment networks (RTP, FedNow)

FinTech domain experience

Kubernetes experience

Benefits

Healthcare Coverage – Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health & dependent care expenses.

401(k) Retirement Plan – Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.

Paid Time Off – Unlimited Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day.

12 weeks of Paid Parental Leave

Maven Family Planning – provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.