Senior Data Engineering Manager

Stash • New York, NY

7d • $180,000 - $220,000 • Hybrid

About The Position

Stash is hiring a Senior Manager, Data Engineering to lead and grow the team responsible for the data platform supporting analytics, data science, operations, and business reporting. This is a hands-on leadership role responsible for setting technical direction for Stash’s AWS-based data platform, developing engineers, and strengthening collaboration with Backend Engineering, Infrastructure, SRE, Analytics Engineering, and Data Science.

The initial priorities are to improve platform reliability, reduce manual operational work, modernize pipeline deployment and monitoring, and establish clear ownership for new data entering the platform. The role requires balancing modernization with simplicity and ensuring that the team can reliably operate the systems it builds.

The position follows a hybrid schedule and requires working on-site in Stash’s New York office at least three days per week.

Requirements

• At least 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 enough to the work to review designs, guide incidents, and unblock difficult technical decisions.
• Strong production experience building or supporting distributed data pipelines using tools such as EMR, Spark, Glue, Delta, Iceberg, or Databricks, and orchestration tools such as Airflow.
• Hands-on experience designing, deploying, and operating data workloads in AWS.
• Strong programming experience, preferably in Python and Scala, and strong SQL experience.
• Experience designing, implementing, and operating real-time or streaming data pipelines.
• A track record of operating business-critical data systems, including observability, incident response, data quality, performance, and cost management.
• Experience introducing or improving CI/CD, Infrastructure as Code, automated testing, code review, and secure deployment practices.
• Strong architectural judgment, including the ability to distinguish actual scaling requirements from process or reliability problems and to favor maintainable systems over unnecessary complexity.
• Experience defining ownership across Data Engineering, Backend Engineering, Infrastructure or SRE, Analytics Engineering, and downstream data consumers.
• Strong people leadership skills, including developing experienced engineers, delegating meaningful ownership, giving direct feedback, and hiring thoughtfully as the team grows.
• Clear communication with technical and non-technical partners, including the ability to explain incidents, architecture decisions, and delayed commitments without obscuring tradeoffs in jargon.
• Sound judgment in a regulated environment, including secure data handling, least-privilege access, auditability, and change control.

Nice To Haves

• Experience working 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 a platform from manual operations toward reliable self-service and automation.
• Experience with Datadog or similar observability platforms for pipelines and infrastructure.
• 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 work, with appropriate validation and security judgment.

Responsibilities

• Lead and grow the Data Engineering team by coaching engineers, setting expectations, creating development opportunities, and fostering ownership, accountability, and technical excellence.
• Own the Data Engineering roadmap, translating company priorities and platform risks into a sequenced plan balancing reliability, automation, security, cost, and new capabilities.
• Improve observability, alerting, runbooks, incident response, service-level expectations, and recovery practices.
• Identify repetitive and fragile operational processes, prioritize them by risk and effort, and automate work that consumes engineering capacity.
• Establish CI/CD, Infrastructure as Code, testing, code review, documentation, and rollback practices for data pipelines and supporting infrastructure.
• Guide architecture and hands-on design for the AWS data platform, including Spark, Airflow, ingestion, distributed processing, storage, and warehouse delivery; improve performance and cost without unnecessary complexity.
• Partner with Backend, Infrastructure, SRE, and Security to ensure new product systems have reliable data contracts, production-ready ingestion, appropriate access controls, and named operational owners.
• Define data quality standards for schemas, keys, grain, semantics, validation, lineage, backfills, and cutovers, preventing source changes from silently affecting downstream metrics or models.
• Partner with Analytics Engineering and Data Science to provide reliable, well-documented platform inputs and clarify boundaries among ingestion, source normalization, business-facing marts, and analytical use cases.
• Evaluate batch, higher-frequency batch, and real-time patterns according to business requirements, operational cost, and team capacity.
• Communicate platform health, risks, priorities, tradeoffs, and progress clearly to technical and business leaders.
• Use AI-assisted development and operational workflows where they improve quality and speed, while protecting sensitive data and taking responsibility for output correctness.

Benefits

• Comprehensive total rewards package comprising compensation (salary and equity) and health care benefits.
• Complimentary subscription to a Stash+ account.
• Flexible work environment combining work from home with in-person collaboration at the NYC office.
• Flexible PTO.
• Annual learning and development reimbursement benefit.
• Work-from-home equipment stipends and home internet subsidy.
• Paid parental leave for birth-giving and non-birth-giving parents, with primary and secondary offerings.
• Enhanced health and wellness benefits through One Medical, Gympass, and Maven Health.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed