Senior Data Engineer

Role overview

Own a major data engineering domain supporting customer engagement, campaign operations, and marketing analytics. The role combines hands-on development of batch and streaming pipelines with architecture, production operations, and privacy governance, turning customer, audience, consent, and campaign information into dependable data products for teams across regions.

Responsibilities

- Design, build, and evolve pipelines that ingest, reconcile, transform, and serve behavioral, audience, campaign, consent, and activation data. - Set architecture, data models, ownership boundaries, and interfaces while accounting for scale, reliability, performance, cost, privacy, and compatibility. - Lead cross-functional delivery, write production-quality code, and coordinate safe integrations with engineering, marketing, and operations teams. - Establish reusable data quality and engineering standards; investigate incidents across distributed processing, storage, and cloud services and prevent recurrence. - Build privacy and governance controls into systems, including consent propagation, data minimization, access restrictions, deletion workflows, and auditable lineage. - Review architecture and data models, mentor engineers, and guide technical tradeoffs and migrations while maintaining production service.

Requirements

- At least eight years of relevant industry experience and a bachelor’s degree or equivalent; the listing also asks for a master’s degree or equivalent in a related field. - Proven ownership of production data pipelines or distributed data platforms, including complex cross-team initiatives. - Strong Python, SQL, and experience with another modern language such as Java or Go. - Hands-on experience with Apache Spark or similar distributed processing, workflow orchestration such as Airflow, and cloud data platform services. - Knowledge of lake or lakehouse architecture, object storage, cloud warehouses, and open table formats such as Apache Iceberg. - Strong data modeling and operational skills, including schema evolution, incremental processing, idempotency, replay, late data, failure recovery, and production debugging.

Nice to have

- Experience with marketing technology and large-scale consumer data, including customer data platforms, identity resolution, audience activation, reverse ETL, or attribution. - Background building high-throughput streaming systems, with attention to delivery guarantees, consumer lag, schema management, and replay.

Benefits and work setup

- The listing states eligibility for equity and benefits and gives a base salary range of USD 168,000–270,250, with pay based in part on location and experience.