Opportunity Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list. Find me work
dataroles

Senior Manager, Data Platform - T0

Airwallex airwallex.com Open · verified Oct 24, 2026
Hybrid San Francisco Full-time Senior Data Engineering

At a glance

Senior Data Engineering role at Airwallex. San Francisco · full-time · $255,000–$300,000 base.

SalaryStated by Airwallex
$255,000 – $300,000
Base salary for this role, in USD per year, as published in the posting.
This role, from AirwallexOur estimate for the market: $181,125–$232,500Median $205,000
Above the market median of $205,000 for senior data engineering roles in San Francisco.
Worked out from 27 postings that stated pay, median $205,000. Last updated Oct 21, 2026.
RoleData Engineering
SenioritySenior
LocationSan Francisco
WorkplaceHybrid
EmploymentFull-time
Base pay$255,000–$300,000
PostedOct 1, 2026 · 3w ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Lead and develop the data platform team, setting technical direction and giving engineers clear ownership and career support
  • Design ingestion for financial data from payment, banking, billing and ERP systems, with dependable replay and recovery
  • Guide the Databricks lakehouse and canonical financial models that turn source records into consistent accounting data
  • Move processing toward near-real-time flows and lead legacy pipeline migrations with validation and rollback plans
  • Set platform standards for data quality and production reliability, while coordinating with product, accounting and infrastructure teams

What you bring

  • At least eight years in data platform, backend or infrastructure engineering, including substantial team leadership
  • A track record managing senior engineers and technical leads while building teams that work autonomously
  • Strong practical knowledge of Python, SQL, Spark, Databricks, Delta Lake, dbt and modern lakehouse systems
  • Experience delivering dependable ingestion, streaming, orchestration and production infrastructure, including GCP and related tools

Who this fits

This is a senior engineering management role for someone who can lead engineers while setting direction for a financial data platform. The role is based in San Francisco.

From the employer

About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.

We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.

We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

About the Team

This team designs intelligent, autonomous systems that eliminate financial operations for companies globally. We automate everything from bookkeeping and reconciliation to tax, payroll, forecasting, and document understanding: turning hours of work into seconds. The team blends deep research pedigree with proven industry experience. We operate with high standards, are tool-agnostic, and expect engineers to own problems end-to-end. We collaborate closely, push boundaries responsibly, and ship exceptional work quickly. You’ll solve unprecedented technical challenges using unique, end-to-end financial datasets no one else in the industry has.

About the Role

As a Senior Manager of Data Platform Engineering, you’ll lead the team responsible for the data backbone of our financial systems. You’ll set the technical direction for high-volume financial data ingestion, our Databricks lakehouse, data orchestration, canonical financial models, and the infrastructure that makes our data platform reliable, scalable, and increasingly real-time.

You’ll combine strong technical judgment with people leadership—building a high-performing engineering organization, establishing platform standards, driving major migrations, and partnering closely with product, accounting, and platform teams. You’ll help shape a data platform where correctness, auditability, performance, and operational excellence are foundational.

This role is based in San Francisco.

What You'll Do

  • Lead and grow a high-performing data platform engineering team, providing technical direction, mentorship, career development, and clear ownership.

  • Set the technical strategy for high-volume financial data ingestion across payment processors, banks, billing systems, and ERP/GL platforms, with strong guarantees around correctness, replayability, and recovery.

  • Lead the evolution of our Databricks lakehouse using Spark, Delta Lake, Unity Catalog, dbt, Python, and SQL, optimizing for scale, performance, reliability, and cost.

  • Define standards for data contracts, schema evolution, drift detection, data quality, and canonical financial models.

  • Evolve the platform from batch toward near-real-time processing using Kafka, CDC, micro-batching, incremental processing, and Dagster orchestration.

  • Own the architecture of canonical financial models that transform complex source data into consistent financial objects and relationships powering our accounting engine.

  • Partner with infrastructure and platform teams to build reliable production foundations across observability, alerting, incident response, recovery, and operational readiness.

  • Guide infrastructure strategy across GCP, Terraform, Kubernetes/GKE, Helm, GitOps, and CI/CD.

  • Lead migrations from legacy pipelines to the lakehouse, with rigorous parity validation, staged rollouts, and clear rollback strategies.

  • Drive performance and cost optimization across PostgreSQL, Databricks, and large-scale data workloads.

  • Partner with product, accounting, ML, and platform leadership to translate business needs into scalable data platform capabilities.

  • Set technical direction through architecture reviews, design documents, engineering standards, and long-term platform roadmaps.

  • Champion AI-assisted engineering practices that improve team velocity while maintaining high standards for code quality, testing, security, and reliability.

What You’ll Need to Have

  • 8+ years of experience in data platform, backend, or infrastructure engineering, including significant experience leading engineering teams.

  • Proven experience managing and developing senior engineers and technical leads and building strong, autonomous teams.

  • Deep expertise in data platforms, distributed systems, data modeling, and production data pipelines.

  • Strong experience with Python and SQL, plus hands-on experience with Spark, Databricks, Delta Lake, dbt, and modern lakehouse architectures.

  • Experience building reliable ingestion systems with large-scale backfills, incremental processing, checkpointing, rate-limit handling, idempotency, and failure recovery.

  • Strong understanding of streaming and event-driven architectures, including Kafka, CDC, and micro-batching.

  • Experience with data orchestration platforms such as Dagster and designing for freshness, partitioning, and incremental computation.

  • Experience optimizing PostgreSQL and analytical workloads for performance and cost.

  • Experience operating production infrastructure on GCP, with familiarity with Terraform, Kubernetes/GKE, Helm, GitOps, and CI/CD.

  • Strong understanding of observability, reliability engineering, and production operations.

  • Excellent technical communication skills, with the ability to influence architecture and engineering decisions across teams.

  • Experience leading complex technical migrations and balancing long-term platform strategy with near-term business priorities.

  • Passion for building teams and infrastructure that power reliable, scalable, mission-critical financial systems.

Applicant Safety Policy: Fraud and Third-Party Recruiters

To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page.

Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.

Equal opportunity

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering$250k+

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.