Senior Data Engineering Manager (AWS)

Location: Hybrid in New York, United States; on-site in the New York office at least three days per week.

Base salary: $180,000–$220,000 per year, plus equity and benefits.

Company

hirify.global is a fintech company focused on helping everyday Americans invest and build wealth through education, advice, and financial products.

What you will do

• Lead and grow the Data Engineering team, including coaching, hiring, delegation, performance expectations, and technical development.
• Own the Data Engineering roadmap and balance reliability, automation, security, cost, and new platform capabilities.
• Improve observability, alerting, runbooks, incident response, service-level expectations, recovery practices, and data-platform reliability.
• Modernize delivery through CI/CD, Infrastructure as Code, testing, code review, documentation, rollback practices, and operational automation.
• Guide the AWS data-platform architecture across ingestion, distributed processing, storage, warehouse delivery, and batch or real-time patterns.
• Define data ownership and quality standards with Backend Engineering, Infrastructure, SRE, Security, Analytics Engineering, Data Science, and downstream consumers.

Requirements

• 8+ years of experience in data engineering, platform engineering, or a related field, including experience leading or managing data engineers.
• Experience leading a small team while remaining close to the work through design reviews, incident guidance, and difficult technical decisions.
• Strong production experience with distributed data pipelines and tools such as EMR, Glue, Delta, Iceberg, Databricks, and orchestration tools.
• Hands-on experience designing, deploying, and operating data workloads in AWS, with strong programming experience in Python and Scala and strong SQL skills.
• Experience designing, implementing, and operating real-time or streaming data pipelines.
• Experience operating business-critical data systems, including observability, incident response, data quality, performance, and cost management.
• Experience improving CI/CD, Infrastructure as Code, automated testing, code review, and secure deployment practices.
• Strong architectural judgment, maintainability focus, cross-functional ownership design, and clear communication with technical and non-technical partners.
• Experience developing experienced engineers, delegating ownership, giving direct feedback, and hiring as the team grows; sound judgment in regulated environments, including secure data handling, least-privilege access, auditability, and change control.

Nice to have

• Experience in fintech, financial services, brokerage, banking, or another regulated environment.
• Experience supporting production data science or machine-learning workflows.
• Working knowledge of dbt and modern analytics engineering practices.
• Experience evolving platforms from manual operations toward reliable self-service and automation.
• Experience with Datadog or similar observability platforms.
• Experience evaluating or implementing higher-frequency or real-time data patterns when justified by the use case.
• Experience using AI coding assistants or agentic workflows in production engineering with appropriate validation and security judgment.

Culture & Benefits

• Hybrid work combining work from home with in-person collaboration at the NYC office.
• Comprehensive total rewards package with salary, equity, healthcare, and enhanced health and wellness benefits.
• Flexible PTO, paid parental leave, and an annual learning and development reimbursement benefit.
• Work-from-home equipment stipends and a home internet subsidy.
• Inclusive workplace focused on diversity, equity, and inclusion, with reasonable accommodations available during the application process.