Big Data Engineer - Data Platform, Global E-Commerce

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.​

Job highlights

Career growth opportunity, Paid leave, Industry experts, Meals provided

Responsibilities

Team Introduction

The mission of the Data Platform Singapore Business Partnering (DPSG BP) team is to empower the business with data. Our goal is to build a Data Warehouse that can cater to batch and streaming data, Data Products that provide useful information to build efficient data metrics & dashboards which will be used to make smarter business decisions to support business growth. If you're looking for a challenging ground to push your limits, this is the team for you!

Responsibilities

- Translate business requirements & end to end designs into technical implementations and responsible for building batch and real-time data warehouse.

- Manage data modeling design, writing, and optimizing ETL jobs.

- Collaborate with the business team to building data metrics based on data warehouse.

- Responsible for building and maintaining data products.

- Involvement in rollouts, upgrades, implementation, and release of data system changes as required for streamlining of internal practices.

- Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software.

- Apply data mining, data modelling, natural language processing, and machine learning to extract and analyse information from large structured and unstructured datasets.

- Visualise, interpret, and report data findings and may create dynamic data reports as well.

Qualifications

Minimum Qualification(s):

- At least 3 years in software engineering and 2 years of relevant experience in data engineering.

- Proficient in creating and maintaining complex ETL pipelines end-to-end while maintaining high reliability and security.

- Familiar with data warehouse concept and have production experience in modeling design.

- Familiar with at least 1 distributed computing engine (e.g. Hive, Spark, Flink).

- Familiar with at least 1 NoSQL database is a plus (e.g. HBase).

Preferred Qualification(s):

- Excellent interpersonal and communication skills with the ability to engage and manage internal and external stakeholders across all levels of seniority.

- Strong collaboration skills with the ability to build rapport across teams and stakeholders.

Skills

Data Warehousing Design, internal control requirements, Building Rapport, Metrics Data, Pipeline Management, Team Development, Data Warehouse Systems, NoSQL, Data Engineering, Data and Information Visualisation, Software Upgrades, Data Model Design, Writing, Product Data Management, relationships with internal stakeholders