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As data product engineers in Revenue function, our mission is to build real-time and offline data products to make data better accessible and reliable while leveraging the largest-scale data processing technologies in the world -- and then apply them to the Revenue’s most critical and fundamental data problems.
Learn more about some of the challenges we tackle on this team:
- Building a Petabyte-scale Data Warehouse (Google Cloud Next '18) https://youtu.be/APBF9Z3uBCc
- How Twitter Migrated its On-Prem Analytics to Google Cloud (Google Cloud Next '18) https://youtu.be/sitnQxyejUg
What You’ll Do:
As a member of the Data Product Engineering team, you will work closely with product teams to build mission-critical data pipelines and products that are ‘source of truth’ for Twitter’s fundamental revenue data, as well as modern data warehouse solutions. You will collaborate closely with Ads Data Science, Machine Learning engineers, product managers, and many other data consumers across the company.
You will be a part of an early-stage team and have a significant stake in defining its future with a considerable potential to impact all of Twitter’s revenue and hundreds of millions of users.
You will be among the earliest adopters of bleeding-edge data technologies, working directly with Revenue Science and Revenue Platforms teams to integrate your services at scale.
Your efforts will reveal invaluable business and user insights, leveraging vast amounts of Twitter revenue data to fuel numerous teams including Ads Analytics, Ads Experience, Ads Data Science, Marketplace, Targeting, Prediction, and many others.
Who You Are:
You are passionate about data and driven to take the data organization challenges at the Twitter’s data scope.
What you’ll need:
- Strong programming and algorithmic skills
- Experience with data processing (such as Hadoop, Spark, Pig, Hive, MapReduce etc).
- Proficiency with SQL (Relational, Redshift, Hive, Presto, Vertica)
- Data Modeling and ER models
- Ability in managing and communicating data project plans and requirements to internal clients
Nice to have:
- Experience writing Big Data pipelines, as well as custom or structured ETL, implementation and maintenance
- Experience with large-scale data warehousing architecture and data modeling
- Proficiency with Java, Scala, or Python
- Experience with GCP (BigQuery, BigTable, DataFlow)
- Experience with Druid or Apache Flink
- Experience with real-time streaming (Apache Kafka, Apache Beam, Heron, Spark Streaming)
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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