Director, Data Engineering (AI)

Location: US - Bellevue, WA; at least 3 days per week in the office are required. The position is performed in an office setting and requires 5–10% travel.

Estimated salary: $197,200–$315,700 USD per year, potentially including sales incentive payments. The position may also be eligible for bonus and equity.

Company

hirify.global is a global payments technology company facilitating transactions between consumers, merchants, financial institutions, and government entities across more than 200 countries and territories.

What you will do

• Lead the design, development, and deployment of scalable and secure data pipelines, platforms, and ML/AI infrastructure.
• Oversee the integration of structured and unstructured data sources for advanced analytics, machine learning, and AI initiatives.
• Evaluate and implement tools and technologies that improve productivity, scalability, and effectiveness across data engineering.
• Establish data engineering best practices, technical standards, governance, quality standards, security, privacy, compliance, performance, scalability, and availability.
• Define and report KPIs, lead incident response and root cause analysis, and ensure high availability and reliability of data platforms.
• Collaborate on business solutions and technical roadmaps, mentor and grow data engineers, and partner with senior leadership on enterprise data strategy.

Requirements

• 10+ years of relevant work experience with a bachelor’s degree, or 13+ years of relevant work experience.
• Excellent problem-solving and analytical skills, with the ability to form and advocate for an independent viewpoint.
• Ability to foster a GenAI-first culture and integrate generative AI into engineering workflows.

Nice to have

• 12+ years of work experience with a bachelor’s degree, or 8–10 years with an advanced degree, or 6+ years with a PhD.
• Experience leading large-scale data engineering teams and projects in complex enterprise environments.
• Experience with data architecture, ETL/ELT pipelines, data warehousing, real-time data processing, data modeling, governance, and quality frameworks.
• Experience with big data technologies such as Spark, Kafka, and Hadoop, plus open-source data engineering tools or communities.
• Hands-on development or architectural experience with real-time and streaming infrastructure, DevOps, Apache Kafka, Apache Pulsar, AWS Kinesis, Google Cloud Pub/Sub, Apache Flink, Apache Spark Streaming, Kafka Streams, or Ray.
• Deep knowledge of low-latency storage systems, column-oriented databases, and OLAP query engines such as Apache Pinot, Apache Iceberg, ClickHouse, Cassandra, or Redis.
• Experience building multi-tenant streaming platforms with isolation, rate limiting, dynamic resource allocation, zero-downtime schema evolution, Protobuf, or Avro.
• Experience implementing SLOs, SLAs, error budgets, distributed tracing, and monitoring with tools such as Prometheus, Grafana, Datadog, or OpenTelemetry.
• Experience delivering high-impact data solutions, designing and building ML infrastructure to train or serve models, and working with Data and AI.
• Experience in financial services, payments, or another highly regulated industry.
• Experience mentoring and developing engineering talent, driving operational excellence, and applying standard methodologies.
• Master’s or PhD in Computer Science or a related technical discipline.
• Experience with large open-source projects, preferably ClickHouse, Redis, Flink, Kafka, or Ray, and contributions to open-source data engineering tools or communities.

Culture & Benefits

• Work in a global payments technology environment focused on large-scale impact and continuous learning.
• Medical, dental, vision, 401(k), FSA/HSA, life insurance, paid time off, and wellness program may be available.
• Generative AI tools such as ChatGPT and Microsoft Copilot are part of digital work expectations.
• Work hours vary according to department needs.