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Sr. Software Engineer, Data

Slack is looking for expert data engineers to join our Insights product team. You will be working cross-functionally with product management, design, business domain experts, analytics, and engineering teams to build insights products for Slack’s customers. In this role you will design, implement and scale data pipelines that transform billions of records into actionable data models that enable data insights products.

You have deep technical skills, be comfortable contributing to a nascent data ecosystem, and building 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

  • You’ll own technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems.  
  • You’ll participate in the strategic development of methods, techniques, and evaluation criteria for projects and programs.
  • You'll translate business requirements into data models that are easy to understand and used by different disciplines across the company
  • You'll own the design, implementation and building of pipelines that deliver data with measurable quality under the SLA
  • You'll brainstorm with product management, business domain experts, data analysts and engineering teams to build data sets used to power insights products for Slack customers
  • You'll own and document foundational company metrics with a clear definition and data lineage
  • You'll identify, document and promote best practices
  • You'll be a champion of the overall strategy for data governance, security, privacy, quality and retention that will satisfy business policies and requirements

What you should have

  • 7+ years of experience working in data architecture, data modeling, master data management, metadata management
  • Recent accomplishments working with relational as well as NoSQL data stores, methods and approaches (logging, columnar, star and snowflake, dimensional modeling)
  • You can lead technical architecture discussions and help drive technical decisions within your team.
  • Proven track record in scaling and optimizing schemas, performance tuning SQL and ETL pipelines in OLAP and Data Warehouse environments
  • Demonstrated skills with either Python or Java programming language
  • Familiar with data governance frameworks, SDLC, and Agile methodology
  • Excellent written and verbal communication and interpersonal skills, and ability to effectively collaborate with 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

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 aim to be smart, humble, hardworking and, above all, collaborative. If this sounds like a good fit for you, why not say hello?

 


Slack is a layer of the business technology stack that brings together people, data, and applications – a single place where people can effectively work together, find important information, and access hundreds of thousands of critical applications and services to do their best work. From global Fortune 100 companies to corner markets, businesses and teams of all kinds use Slack to bring the right people together with all the right information. Slack is headquartered in San Francisco, CA and has offices around the world. For more information on how Slack makes teams better connected, visit slack.com.

Ensuring a diverse and inclusive workplace where we learn from each other is core to Slack’s values. We welcome people of different backgrounds, experiences, abilities and perspectives. We are an equal opportunity employer and a pleasant and supportive place to work.

Come do the best work of your life here at Slack.