Promoted dramatically improves search and discovery relevance and ads quality at scale, like at our customers Upwork, Eventbrite, and Outschool. We combine the best of traditional ML and streaming data infra with the latest in LLM AI to optimize the balance between relevance, revenue, and profitability. We're ex-Google, Meta, and Pinterest ads engineers, and we've built this before together.

When you join Promoted, you’ll get the benefits of:

• San Francisco Office - Our office space is open and available
• Healthcare Plans - We have options for you and your family
• FSA/HSA - You can opt into these savings plans
• Dependant Care Account - For eligible care savings
• 401k - We offer it and match your first 6%
• PerkSpot Account - Trusted employee discounts
• Competitive and transparent compensation

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, mental or physical disability, gender identity or Veteran status.

Data Stream Processing Software Engineer

Ship innovations in streaming data processing at publicly traded company data scales but at startup scale shipping velocities! If you love Flink, then this role is the perfect fit for you.

Responsibilities

• Leverage Apache Flink to develop robust and efficient stream processing jobs and tackle challenges related to data skew, out-of-order events, and other intricacies of streaming data. Must be an expert with Apache Flink.
• Architect and implement near real-time ingestion pipelines for data lakes.
• Maintain and optimize the data infrastructure for streaming systems.
• Collaborate closely with cross-functional team members to ensure seamless data processing.

Requirements

• Enthusiasm for working in a startup environment with a small, dedicated team.
• Proficiency in at least one programming language, such as Java, Scala, Kotlin, or Python.
• Hands-on experience with big data systems such as Apache Spark, Apache Flink, and Apache Kafka.
• Knowledge of common data storage formats such as Avro, Proto, and Parquet.
• Experience with at least one cloud platform, such as AWS or GCP.
• Familiarity with Kubernetes and experience with tools such as Helm, Prometheus, and Grafana.

Preferred Qualifications

• Familiarity with data analytics tools such as Apache Hive, ClickHouse, Presto, Trino, or AWS Redshift.
• Experience data lake formats such as Apache Iceberg, Hudi, and Paimon.
• Experience with DevOps practices, IoC, and Terraform.
• Background in Machine Learning or Recommendation Systems.