Responsibilities
About the team
The success of TikTok's data business model hinges on the supply of a large volume of high quality labeled data that will grow exponentially as our business scales up. However, the current cost of data labeling is excessively high. The Data Solutions Team uses quantitative and qualitative data to guide and uncover insights, turning our findings into real products to power exponential growth. The Data Solutions Team responsibility includes infrastructure construction, recognition capabilities management, global labeling delivery management.

About the role
As Data Engineer, you will be working on cutting-edge challenges in the big data and Al industry which requires strong passion and capability of innovation. You will collaborate closely with cross-functional teams to understand business requirements and translate them into technical solutions.
Responsibility
1. Design, build, and maintain robust, scalable, and efficient data pipelines for ingesting, processing, and transforming large volumes of data to meet both immediate and long-term business needs.
2. Define the technical strategy and roadmap for data engineering projects in alignment with business objectives, actively evaluate and bring in industry best practices and state-of-the-art technical approaches, and timely update the strategy according to the rapid change of the industry;
3. Own and drive data engineering projects by leveraging both internal and cross-functional resources, setting meaningful and challenging targets, and achieving them with innovative approaches;
4. Ensure data governance and quality, establishing processes to manage and protect the integrity of data across systems.
5. Translate business requirements into actionable data solutions, maintaining a strong understanding of business needs and using data to generate impactful insights for decision-making.
6. Support business intelligence efforts by designing and implementing data warehousing solutions and building interactive dashboards for real-time business analysis.

Qualifications
Minimum Qualifications
1. Bachelor's or Master's degree in Computer Science, Engineering, or related field;
2. 3+ years of experience (or equivalent) in data engineering, with a strong track record of building and managing large-scale, production-grade data pipelines.
3. Proficiency in Python and SQL for data processing and automation; experience with Java or Scala is a plus.
4. Hands-on experience with big data frameworks such as Apache Spark, Hadoop, Kafka, or similar technologies. Experience in performance tuning and optimization of data pipelines and large-scale distributed systems.
5. Strong knowledge of database and data warehousing concepts, including star schema, dimensional modeling, ETL/ELT frameworks, and schema design.
6. Familiarity with data governance, data quality frameworks, and best practices in data validation, lineage, and metadata management.
7. Experience using data visualization tools such as Tableau, Power Bl, or internal platforms to support business insights.

Preferred Qualifications
1. Familiarity with real-time data processing technologies such as Flink and others.
2. Strong communication and interpersonal skills, with the ability to work effectively with both technical and non-technical stakeholders.

Trust & Safety
Content that this role interacts with includes images, video, and text related to every-day life, but it can also include (but is not limited to) bullying; hate speech; child safety; depictions of harm to self and others, and harm to animals. Hence, it is possible that this role will be exposed to harmful content on a daily basis.

TikTok recognises that keeping our platform safe for the TikTok communities is no ordinary job which can be both rewarding and psychologically demanding and emotionally taxing for some. This is why we are sharing the potential hazards, risks and implications in this unique line of work from the start, so our candidates are well informed before joining.

We are committed to the wellbeing of all our employees and promise to provide comprehensive and evidence-based programs, to promote and support physical and mental wellbeing throughout each employee's journey with us. We believe that wellbeing is a relationship and that everyone has a part to play, so we work in collaboration and consultation with our employees and across our functions in order to ensure a truly person-centred, innovative and integrated approach.

About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an Always Day 1 mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion
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.

Data Engineer - Data Governance