Senior Data Engineer, Analytics

TikTok

Seattle, WA, USA

Full time

Data + Analytics

Sep 5

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul, and Tokyo.


Why Join Us:

At TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.


The DCC Data Science team within Monetization Integrity (MI) is seeking a bright and endlessly curious data expert to join our data engineering practice. This group is responsible for the infrastructure to support large amounts of unstructured and structured data for analytical projects and upstream machine learning models.


About the Role:

As an Data Engineer, you will have significant responsibility and influence in shaping its strategic direction. This role is inherently multi-functional, and the ideal candidate will work across disciplines. We are looking for someone with a love for data and the ability to iterate quickly. This position involves working with small engineering teams to develop large-scale Data Pipelines for Machine Learning and Analytical solutions using Big Data technologies. Successful candidates will have strong engineering skills and communication and a belief that data-driven processes lead to phenomenal products.


Responsibilities:

What You'll Need:

- The perfect candidate will have strong data infrastructure and data architecture skills, strong operational skills to drive efficiency and speed, strong project management leadership, and a strong vision for how data engineering can proactively improve companies.


What You'll Do:

- Drive the design, building, and launching of new data models, data pipelines, and data products in production.

- Manage the delivery of high impact dashboards and data visualizations. Define and manage SLA and data quality for all data sets and processes running in production.

- Build cross-functional relationships to understand data needs, build key metrics and standardize their usage across the organization.

Qualifications

- 3+ years of experience working in data engineering, business intelligence or a related domain

- Proficiency in distributed data processing using Big Data technologies like Spark/Scala, Java, Hadoop/HDFS/AWS/S3, Cassandra and Kafka

- Experience using tech solutions like Git, Gradle, Airflow, and Kubernetes to build & deploy apps and jobs on cloud-hosted services

- Proficiency in data modeling, data design, SQL, and NoSQL databases

- Strong background in algorithms and data structures

- Experience working with PII and GDPR data

Preferred:

- Experience in a consumer web or mobile company

- Ability to communicate effectively, both written and verbal, with technical and non-technical partners

- Ability to deliver consistent high quality results while working in a dynamic & fast environment

- Passionate, curious, and seeking to tackle every day problems with innovation


TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.


TikTok is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to us at USRC@tiktok.com.

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