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Products and Technology
Slack is looking for expert Data Engineers to join our Insights team, focusing on product experimentation. In this role, you will be working cross-functionally with our Data Engineering group, business domain experts, analytics, and engineering teams to design, implement and ensure the reliability of our Experiment data model. You will design, implement and scale data pipelines that transform billions of records into actionable data models that enable product insights and decisions.
You will lead initiatives to formalize data governance and management practices, rationalize our information lifecycle and key experiment metrics. You will provide mentorship and hands-on technical support to build trusted and reliable metrics.
You have deep technical skills, you are comfortable contributing to a nascent data ecosystem, and you can build a strong data foundation for the company. You are a self-starter, detail and quality oriented, and passionate about having a huge impact at Slack.
What You Will Be Doing
- Own the technical strategy for significant portions of Slack’s experiments data model that meets the needs of a diverse group of stakeholders and use cases
- Provide guidance and mentorship to the team against a data modeling strategy that balances speed, extensibility, and reliability
- Lead broad cross functional efforts across data engineering that up-level Slack’s ability to leverage data and drive insights
- Set measurable quality and SLA goals for the experiments pipeline to create a culture of reliability and trust
- Partner with business domain experts, product managers, and engineering teams to build foundational data sets and tools that are trusted, well understood, aligned with business strategy. Partner with teams across Slack on various feature rollouts and initiatives
- Be a champion of the overall strategy for data governance and information architecture of our experiments data model
- Identify, document and promote data engineering standard methodologies throughout Slack
- Mentor other engineers and deeply review code
What You Should Have
- 7+ years of experience working in experimentation, A/B testing, data architecture, data modeling, master data management, metadata management
- Able to lead technical architecture discussions and drive technical decisions with data engineers and stakeholders
- A strong grasp of data fundamentals for methods and approaches (logging, columnar, star and snowflake, dimensional modeling)
- Proven track record in scaling and optimizing data warehouses, both logically and technically
- Demonstrated skills with either Python or Java programming language
- Strong communication and interpersonal skills with the ability to effectively collaborate with both technical and business partners
- Hands-on experience with Big Data technologies (e.g Hadoop, Hive, Spark) is a big plus
- Bachelor's degree in Computer Science, Engineering or a related field, or equivalent training, fellowship, or work experience
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