Senior Manager Data Engineering

San Francisco OR Remote US/Canada

Full Time Senior-level / Expert
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Posted 3 weeks ago

At Scribd (pronounced “scribbed”), we believe reading is more important than ever. Join our cast of characters as we build the world’s largest and most fascinating digital library: giving subscribers access to a growing collection of ebooks, audiobooks, magazines, documents, Scribd Originals and more. In addition to works from major publishers and top authors, our community includes over 1.4M subscribers in nearly every country worldwide.
What you'll do
Data quality and integrity are two areas of focus for your work in our existing, organically-grown data infrastructure. You would be helping to build the data engineering team, and would work with product teams to clarify what data pipelines are important, and then work with them to build process, tooling, and technology to ensure that downstream customers can trust the data they're consuming. Depending on the project, this might involve collaboration with the Data Science and Content Engineering teams to identify business-critical Hive tables, or working with Core Platform to suggest better approaches for scaling streaming data sets. Almost everything you would be working on would be to increase the "customer satisfaction" for internal customers of Scribd data.
You'll have (Requirements)
• Strong written and verbal communication skills (we're remote!)• Strong mentoring skills and experiencing training and educating teammates or colleagues.• Experience building and delivering high quality data systems using tools from the Hadoop or Spark ecosystem• Experiencing structuring large scale datasets in S3.• Fluency with at least one dialect of SQL (MySQL and Spark SQL preferred)• Ability to develop software, whether scripts for shuffling data around, batch tasks, or stream processing units.
Nice to Have (Bonus Points)
•  Streaming platform experience, typically based around Kafka, Spark, Storm, Beam•  Working knowledge of how to build, train, and deploy ML models.•  Strong understanding of AWS data platform services and their strengths/weaknesses.•  Opinions on what data integrity means and how to scale it up the organization. •  Working knowledge of Sqoop, Hive, Impala, and HDFSBenefits, Perks and Wellbeing at Scribd
• Healthcare Benefits: Scribd pays 100% of employee’s Medical, Vision, and Dental premiums and 70% of dependents• Leaves: Paid parental leave, 100% company paid short-term/long-term disability plans, and milestone Sabbaticals• 401k plan through Fidelity,  plus company matching with no vesting period• Diversity, Equity, & Inclusion hiring best practices• Stock Options - every employee is an owner in Scribd! • Generous Paid Time Off, Paid Holidays, Flexible Sick Time, Volunteer Day + office closure between Christmas Eve and New Years Day• Referral bonuses• Professional development: generous annual budget for our employees to attend conferences, classes, and other events• Company-wide Diversity, Equity & Inclusion training• Learning & Development and Coaching programs• Monthly Wellness, Connectivity & Comfort Benefit• Concern mental health digital platform• Work-life balance flexibility• Employee Resource Groups that build community and support among employees• Company events + Scribdchats• Free subscription to Scribd + gift memberships for friends & family• Monthly inclusive multi-cultural celebrations & learning opportunities
Want to learn more? Check out our office and meet some of the team at www.linkedin.com/company/scribd/life
Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
Job tags: AWS Data pipelines Engineering Hadoop Healthcare Kafka ML MySQL Spark SQL
Job region(s): North America Remote/Anywhere
Job stats:  20  1  0
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