Salesforce, Inc..
Slack is looking for a staff software engineer to join the Data Ingestion Team. As part of the Data Engineering organization, we build and operate the platform that ingests data from various sources into our Data Warehouse with both streaming and batch approaches. Currently, our infrastructure handles 180PB+ of storage, processes ~1T records a day, 400+ data pipelines and 1000+ Active Airflow DAGs. As Slack’s data grows (along with the number of customers, features and employees), the goal of the team is to build a highly scalable and resilient ingestion platform leveraging modern Streaming and Lakehouse technologies.
As a Staff Engineer, you will play a key role in driving our streaming and lakehouse strategies while also building highly scalable services and tools to help our customers acquire large volumes of high quality data at scale and making customers’ interactions with the ingested data pleasant and productive. You will have deep technical skills, be a self-starter, detail and quality oriented, and passionate about driving data driven decisions and having a huge impact at Slack!
What you will be doing
Design and develop highly scalable and resilient streaming and batch services for ingesting and processing structured and unstructured datasets
Design and implement Slack’s Lakehouse solutions and enable production use cases for customers
Automate and handle the lifecycle of datasets (schema evolution, metadata management, change and backfill management, deprecation and migration).
Improve the data quality and reliability of the pipelines through proper monitoring and alerting.
Comfortably collaborate with cross functional partners and lead technical initiatives independently end to end.
Be a role model and a multiplier, coaching and mentoring other engineers across the org.
Write, review, or provide feedback on a technical design proposal from others.
What you should have
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
You have good experience and knowledge on building and maintaining batch data pipelines using Spark, Airflow, EMR, S3, etc.
You are proficient in object-oriented and/or functional programming languages: SQL, Python, Java/Scala, Go or equivalent
You are skilled at crafting and building robust distributed microservices with tools like Kubernetes, Docker, AWS ECS/EKS, Terraform, etc.
You have strong dedication to code quality, automation and operational excellence: CI/CD pipelines, unit/integration tests.
You have 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
You have high growth expectations for yourself and your team, and a willingness to push yourself and your team to achieve them
Bachelor's degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience
Slack has a positive, diverse, and supportive culture—we look for people who are curious, inventive, and work to be a little better every single day. In our work together we seek to be smart, humble, hardworking and, above all, collaborative.
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Design and develop highly scalable and resilient streaming and batch services for ingesting and processing structured and unstructured datasets
Design and implement Slack’s Lakehouse solutions and enable production use cases for customers
Automate and handle the lifecycle of datasets (schema evolution, metadata management, change and backfill management, deprecation and migration).
Improve the data quality and reliability of the pipelines through proper monitoring and alerting.
Comfortably collaborate with cross functional partners and lead technical initiatives independently end to end.
Be a role model and a multiplier, coaching and mentoring other engineers across the org.
Write, review, or provide feedback on a technical design proposal from others.
What you should have
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
You have good experience and knowledge on building and maintaining batch data pipelines using Spark, Airflow, EMR, S3, etc.
You are proficient in object-oriented and/or functional programming languages: SQL, Python, Java/Scala, Go or equivalent
You are skilled at crafting and building robust distributed microservices with tools like Kubernetes, Docker, AWS ECS/EKS, Terraform, etc.
You have strong dedication to code quality, automation and operational excellence: CI/CD pipelines, unit/integration tests.
You have 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
You have high growth expectations for yourself and your team, and a willingness to push yourself and your team to achieve them
Bachelor's degree in Computer Science, Engineering or related field, or equivalent training, fellowship, or work experience
Slack has a positive, diverse, and supportive culture—we look for people who are curious, inventive, and work to be a little better every single day. In our work together we seek to be smart, humble, hardworking and, above all, collaborative.
#J-18808-Ljbffr