277 Data Engineer jobs in Singapore

Responsibilities

TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok sponsorship of a visa. About the team Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for recommendation system to provide the most stable and best experience for our TikTok users.

We cover almost all short-text recommendation scenarios in TikTok, such as search suggestions, the video-related search bar, and comment entities. Our recommendation system supports personalized sorting for queries, optimizing the user experience and improving TikTok's search awareness.

• Design and implement a reasonable offline data architecture for large-scale recommendation systems
• Design and implement flexible, scalable, stable and high-performance storage and computing systems
• Trouble-shooting of the production system, design and implement the necessary mechanisms and tools to ensure the stability of the overall operation of the production system
• Build industry-leading distributed systems such as storage and computing to provide reliable infrastructure for massive date and large-scale business systems
• Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software
• Applying 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 Qualifications

• Bachelor's degree or above, majoring in Computer Science, or related fields, with at least 1 year of experience
• Familiar with many open source frameworks in the field of big data, e.g. Hadoop, Hive, Flink, FlinkSQL, Spark, Kafka, HBase, Redis, RocksDB, ElasticSearch, etc.
• Experience in programming, including but not limited to, the following programming languages: c, C++, Java or Golang
• Effective communication skills and a sense of ownership and drive
• Experience of Peta Byte level data processing is a plus

Experience

• Hands-on Big Data experience using common open-source components (Hadoop, Hive, Spark, Presto, NiFi, MinIO, K8S, Kafka).

• Experience in stakeholder management in heterogeneous business/technology organizations.

• Experience in banking or financial business, with handling sensitive data across regions.

• Experience in large data migration projects with on-prem Data Lakes.

• Hands-on experience in integrating Data Science Workbench platforms (e.g., KNIME, Cloudera, Dataiku).

• Track record in Agile project management and methods (e.g., Scrum, SAFe).

Skills

• Knowledge of reference architectures, especially concerning integrated, data-driven landscapes and solutions.

• Expert SQL skills, preferably in mixed environments (i.e., classic DWH and distributed).

• Working automation and troubleshooting experience in Python using Jupyter Notebooks or common IDEs.

• Data preparation for reporting/analytics and visualization tools (e.g., Tableau, Power BI or Python-based).

• Applying a data quality framework within the architecture.

Role description

• Datasets and data pipelines preparation, support for Business, data troubleshooting.

• Closely collaborate with the Data & Analytics Program Management and stakeholders to co-design Enterprise Data Strategy and Common Data Model.

• Implementation and promotion of Data Platform, transformative data processes, and services.

• Develop data pipelines and structures for Data Scientists, testing such to ensure that they are fit for use.

• Maintain and model JSON-based schemas and metadata to re-use it across the organization (with central tools).

• Resolving and troubleshooting data-related issues and queries.

• Covering all processes from enterprise reporting to data science (incl. ML Ops).

Roles & Responsibilities

Job Summary:

We are looking for an experienced Big Data Engineer with at least 5 years of experience in managing data pipelines and processing within Big Data environments (e.g. Cloudera Data Platform). The role involves designing, developing, and maintaining data ingestion and transformation jobs to support analytics and reporting needs.

Key Responsibilities:

• Design and develop data ingestion, processing, and integration pipelines using Python, PySpark, and Informatica.
• Analyse data requirements and build scalable data solutions.
• Support testing, deployment, and production operations.
• Collaborate with business and technical teams for smooth delivery.
• Drive automation, standardization, and performance optimization.

Requirements:

• Bachelor's degree in IT, Computer Science, or related field.
• Minimum 5 years' experience in Big Data Engineering.
• Hands-on skills in Python, PySpark, Linux, SQL, and ETL tools (Informatica preferred).
• Experience with Cloudera Data Platform is an advantage.
• Knowledge of data warehousing, Denodo, and reporting tools (SAP BO, Tableau) preferred.
• Strong analytical, problem-solving, and communication skills.

Job Type: Contract

Job Summary:

We are looking for an experienced Big Data Engineer with at least 5 years of experience in managing data pipelines and processing within Big Data environments (e.g. Cloudera Data Platform). The role involves designing, developing, and maintaining data ingestion and transformation jobs to support analytics and reporting needs.

Key Responsibilities:

• Design and develop data ingestion, processing, and integration pipelines using Python, PySpark, and Informatica.
• Analyse data requirements and build scalable data solutions.
• Support testing, deployment, and production operations.
• Collaborate with business and technical teams for smooth delivery.
• Drive automation, standardization, and performance optimization.

Requirements:

• Bachelor's degree in IT, Computer Science, or related field.
• Minimum 5 years' experience in Big Data Engineering.
• Hands-on skills in Python, PySpark, Linux, SQL, and ETL tools (Informatica preferred).
• Experience with Cloudera Data Platform is an advantage.
• Knowledge of data warehousing, Denodo, and reporting tools (SAP BO, Tableau) preferred.
• Strong analytical, problem-solving, and communication skills.

Experience

• Hands-on Big Data experience using common open-source components (Hadoop, Hive, Spark, Presto, NiFi, MinIO, K8S, Kafka).

• Experience in stakeholder management in heterogeneous business/technology organizations.

• Experience in banking or financial business, with handling sensitive data across regions.

• Experience in large data migration projects with on-prem Data Lakes.

• Hands-on experience in integrating Data Science Workbench platforms (e.g., KNIME, Cloudera, Dataiku).

• Track record in Agile project management and methods (e.g., Scrum, SAFe).

Skills

• Knowledge of reference architectures, especially concerning integrated, data-driven landscapes and solutions.

• Expert SQL skills, preferably in mixed environments (i.e., classic DWH and distributed).

• Working automation and troubleshooting experience in Python using Jupyter Notebooks or common IDEs.

• Data preparation for reporting/analytics and visualization tools (e.g., Tableau, Power BI or Python-based).

• Applying a data quality framework within the architecture.

Role description

• Datasets and data pipelines preparation, support for Business, data troubleshooting.

• Closely collaborate with the Data & Analytics Program Management and stakeholders to co-design Enterprise Data Strategy and Common Data Model.

• Implementation and promotion of Data Platform, transformative data processes, and services.

• Develop data pipelines and structures for Data Scientists, testing such to ensure that they are fit for use.

• Maintain and model JSON-based schemas and metadata to re-use it across the organization (with central tools).

• Resolving and troubleshooting data-related issues and queries.

• Covering all processes from enterprise reporting to data science (incl. ML Ops).

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

Positive team atmosphere, Career growth opportunity, Paid leave, 100+ mil users, Meals provided

Responsibilities

Team Introduction

The mission of the Data Platform Singapore Business Partnering (DPSG BP) team is to empower the TikTok 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 Qualifications:

- 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 (e.g. HBase).

Preferred Qualifications:

- 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.

Team Introduction

Ad Data is the cornerstone of every business decision that millions of advertisers make every day on TikTok. Therefore, we are tasked with innovating on daily basis to create and maintain complex systems at large scale and continue expanding the capacity to better serve advertisers growing at exponential pace.

You will share in the ownership of the technical vision and direction for advanced Ad Data products. You will be a part of a team of top notch technical professionals developing scalable systems and with a focus on sustained operational excellence. Members of this team will be challenged to innovate using cutting edge technologies. We are looking for people who are highly motivated by aiming for the highest, moving fast, and changing the way customers use data to drive profitability.

Responsibilities

- Build up advertising data architecture to support creative/creator business growth

- Design, build and launch data ETL models in production and responsible for the data quality

- Manage and govern the data assets in responsible data areas.

- Work with product managers and data analysts to design data-related products/applications.

- Communicate with engineers, product managers and product analysts to understand data needs.

- Support existing streaming and batch system in production, solve the on-call issues.

- Work with data infrastructure to triage infra issues and drive to resolution.

- Support daily project management, assist junior engineers in business and technical problems.

Minimum Qualifications

- Bachelor's degree in technical field, Computer Science or Mathematics.

- 3+ years of experience in data engineering and data architecture supporting large-scale user

- Minimum 3 years of experience in ETL data modeling and metric framework development

- Proven experience in architecting and optimizing data services and model layers

- Familiarity with data governance, quality monitoring, and metric standardization practices

Employment Type: Full-Time
Location : Remote, Singapore
Level: Entry to Mid Level (PhD Required)

Pixalate is an online trust and safety platform that protects businesses, consumers and children from deceptive, fraudulent and non-compliant mobile, CTV apps and websites. We're seeking a PhD-level Big Data Engineer to revolutionize how AI transforms massive-scale data operations.

Our impact is real and measurable. Our software has uncovered:

• Gizmodo: An iCloud Feature Is Enabling a $65 Million Scam
• Washington Post: Your kids' apps are spying on them
• ProPublica: Porn, Piracy, Fraud: What Lurks Inside Google's Black Box Ad Empire

Work at the intersection of big data and AI, where you'll develop intelligent, self-healing data systems processing trillions of data points daily. You'll have autonomy to pursue research in distributed ML systems and AI-enhanced data optimization, with your innovations deployed at unprecedented scale within months, not years.

This isn't traditional data engineering - you'll implement agentic AI for autonomous pipeline management, leverage LLMs for data quality assurance, and create ML-optimized architectures that redefine what's possible at petabyte scale.

AI-Enhanced Data Infrastructure

• Design intelligent pipelines with autonomous optimization and self-healing capabilities using agentic AI
• Implement ML-driven anomaly detection for terabyte-scale datasets

Distributed Machine Learning at Scale

• Build distributed ML pipelines
• Develop real-time feature stores for billions of transactions
• Optimize feature engineering with AutoML and neural architecture search

Education & Research

• PhD in Computer Science, Data Science, or Distributed Systems (exceptional Master's with research experience considered)
• Published research or expertise in distributed computing, ML infrastructure, or stream processing

Technical Expertise

• Core Languages : Expert SQL (window functions, CTEs), Python (Pandas, Polars, PyArrow), Scala/Java
• Big Data Stack : Spark 3.5+, Flink, Kafka, Ray, Dask
• Storage & Orchestration : Delta Lake, Iceberg, Airflow, Dagster, Temporal
• Cloud Platforms : GCP (BigQuery, Dataflow, Vertex AI), AWS (EMR, SageMaker), Azure (Databricks)
• ML Systems : MLflow, Kubeflow, Feature Stores, Vector Databases, scikit-learn + search CV, H2O AutoML, auto-sklearn, GCP Vertex AI AutoML Tables
• Neural Architecture Search: KerasTuner, AutoKeras, Ray Tune, Optuna, PyTorch Lightning + Hydra

Research Skills

• Track record with 100TB+ datasets
• Experience with lakehouse architectures, streaming ML, and graph processing at scale
• Understanding of distributed systems theory and ML algorithm implementation

Preferred Qualifications

• Experience applying LLMs to data engineering challenges
• Ability to translate complex AutoML/NAS research into practical production workflows
• Hands-on project examples of feature engineering automation or NAS experiments
• Proven success in automating ML pipelines, from raw data to an optimized model architecture
• Contributions to Apache projects (Spark, Flink, Kafka)
• Knowledge of privacy-preserving techniques and data mesh architectures

What Makes This Role Unique

You'll work with one of the few truly petabyte-scale production datasets outside of major tech companies, with the freedom to experiment with cutting-edge approaches. Unlike traditional big data roles, you'll apply the latest AI research to fundamental data challenges - from using LLMs to understand data quality issues to implementing agentic systems that autonomously optimize and heal data pipelines.

POSITION OVERVIEW : Big Data Support Engineer

POSITION GENERAL DUTIES AND TASKS :

Skillset

• Up to 5 years of IT experience & 3+ Years on Teradata or Hadoop

• Last 3 years of relevant experience in banking/financial services industry

• Hands-on technologist, strong in SQL, UNIX and Hadoop/Teradata tools and technologies

• Demonstrable analytical skills with good knowledge of Big Data Ecosystem in a Production Support Environment.

• Strong SQL and Unix shell scripting

• Proficient in any job scheduling tool.

• Incident, problem, and service Outage management experience is Plus.

• Good Communication and Articulation Skills

Roles/Responsibilities

He/she is responsible for ensuring system availability and timely deliverables for datamarts for various business unit like Finance, regulatory, Campaign.

• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

• Provide operational support and ensure SLI of Applications

• Troubleshoot Batch Issues & root causes to Mitigate Impacts to SLA

• Proactively Identify and Identify opportunities for preventive Maintenance

• Perform Administration & Optimization to achieve of Optimal System Performance

• Work with Project/Enhancement Teams to Review, Transition for Run Team

• Participate in Disaster Recovery and Business Continuity exercises

• Fine tune applications and systems for high performance and higher volume throughput

• Perform impact analysis of enhancements/projects that will impact supported systems