Staff+ Software Engineer, Data Infrastructure

Responsibilities

Data Governance & Access Control

Design and implement robust access control systems ensuring only authorized users can access sensitive data.

Build infrastructure for permission management, audit logging, and compliance requirements.

Work on IAM policies, ACLs, and security controls that scale across thousands of users and systems.

Financial Data Infrastructure

Build and maintain data pipelines and warehouses powering business-critical reporting.

Ensure data integrity, accuracy, and availability for complex financial systems, including third party revenue ingestion pipelines; manage the external relationships as needed to drive upstream dependencies.

Own the reliability of systems processing revenue, usage, and business metrics.

Cloud Storage & Reliability

Architect disaster recovery, backup, and replication systems for petabyte-scale data.

Ensure high availability and durability of data stored in cloud object storage (GCS, S3).

Build systems that protect against data loss and enable rapid recovery.

Data Platform & Tooling

Scale data processing infrastructure using technologies like Big Query, Big Table, Airflow, dbt, and Spark.

Optimize query performance, manage costs, and enable self‑service analytics across the organization.

Qualifications

• Have 10+ years of experience in a Software Engineer role, building data infrastructure, storage systems, or related distributed systems.
• Have 3+ years of experience leading large‑scale, complex projects or teams as an engineer or tech lead.
• Can set technical direction for a team, not just execute within it.
• Have deep experience with at least one of: strong proficiency in programming languages like Python, Go, Java, or similar; experience with infrastructure‑as‑code (Terraform, Pulumi) and cloud platforms (GCP, AWS).
• Can navigate complex technical tradeoffs between performance, cost, security, and maintainability.
• Have excellent collaboration skills – you work well with both technical and non‑technical stakeholders.
• Strong candidates may also have
• Experience with security and compliance requirements (ITGC, GDPR, financial controls).
• Background in data warehousing, ETL/ELT pipelines, or analytics infrastructure.
• Experience with Kubernetes, containerization, and cloud‑native architectures.
• Track record of improving data reliability, availability, or cost efficiency at scale.
• Knowledge of column‑oriented databases, OLAP systems, or big data processing frameworks.
• Experience working in fintech, financial services, or highly regulated environments.
• Security engineering background with focus on data protection and access controls.
• Technologies We Use
• Data: Big Query, Big Table, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran.
• Storage: GCS, S3.
• Infrastructure: Terraform, Kubernetes, GCP, AWS.
• Languages: Python, Go, SQL.

Deadline to apply: None.

• Logistics
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position.
• Location‑based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas.

However, we aren't able to successfully sponsor visas for every role and every candidate.

If we make you an offer, we will make every reasonable effort to get you a visa.

We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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