Lead Software Engineer-Data Orchestration

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Slack is looking for a Senior Software Engineer to join the Data Orchestration Team. As part of the Data Engineering organization, we build and operate the platform that ingests data into our Data Warehouse, and we build and maintain our low-latency, high-throughput analytics with OLAP DB. We write software to manage the ingestion for thousands of stateful hosts and stateless real time logging events. Currently, our infrastructure handles 65PB+ of storage, processes ~900B records a day, 400+ ETL pipelines and 1300+ 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 to acquire high quality data efficiently and provide easy to use workflow and orchestration capabilities for our downstream customers so that they can focus on their strengths. 

You will build scalable services and tools to help partners implement, deploy and analyze data assets with a high level of autonomy and limited friction. You will play a meaningful role in making partner interactions with the Data Warehouse 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:

• Develop and maintain our real time analytics/low latency data access layer built on top of modern OLAP solutions
• Optimize the end-to-end workflow for data users at Slack (from crafting libraries to schedule data pipelines and access data assets).
• Improve the data quality and reliability of the pipelines through properly monitoring and failure detection.
• Comfortably collaborate with cross functional partners and lead technical initiatives 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.

Desired Skills:

• 5+ years of experience in data engineering or data infrastructure with a proven ability to lead design and implementation of complex solutions
• Experience in real time analytics/low latency data access layer with OLAP stores such as Apache Pinot or Apache Druid is a huge plus.
• Experience operating Airflow or other orchestration tools and upholding best practices for workflow management systems.
• Experience working with cloud infrastructure (AWS preferred).
• You have extensive experience of building and maintaining large scale ETL pipelines and in-depth knowledge of various big data frameworks and architectures
• Ability to identify and quantify high-value initiatives, break them down into milestones and drive execution
• Ability to context switch and take fast action serving on monthly oncall rotation for both internal customer escalations and automated system page
• You are skilled at crafting and building robust distributed microservices with tools like Docker, Kubernetes, AWS ECS/EKS etc.
• You have strong dedication to code quality, automation and operational excellence: CI/CD pipelines, unit/integration tests.
• You are proficient in object-oriented and/or functional programming languages: Python, Java/Scala, Chef, Terraform
• 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

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