Design and develop highly scalable and resilient streaming and batch pipelines for ingesting and processing structured and unstructured datasets
Design and implement Slack’s Lakehouse solutions and enable production use cases for customers
Improve the reliability and performance of the services/pipelines through AI assisted and/or Agentic solutions and tools.
Automate and handle the lifecycle of datasets (schema evolution, metadata management, change and backfill management, deprecation and migration).
Collaborate with cross functional partners and lead technical initiatives independently end to end.
Write, review, or provide feedback on a technical design proposal from others.

U.S. citizenship and willing to undergo a background check for GovSlack authorization
7+ years of software/data engineering experience, including experience with building applications using Streaming and Lakehouse technologies, e.g. Kafka/Kafka Connect, Flink/Spark Streaming, Iceberg/Hudi/Delta or equivalent
hands-on experience and knowledge on building and maintaining batch data pipelines using Spark, Airflow, EMR, S3 or equivalent
proficient in object-oriented and/or functional programming languages: SQL, Python, Java/Scala, Go or equivalent
skilled at crafting and building robust distributed microservices with tools like Kubernetes, Docker, AWS ECS/EKS, Terraform, Grafana, etc.
familiar with AI-assisted software development and automation and have hands-on experience of Claude Code/Codex or equivalent
excellent written and verbal communication and interpersonal skills; able to effectively collaborate with cross-functional partners and explaining sophisticated technical concepts to non-technical stakeholders.

Staff Software Engineer, Data Ingestion

Key skills