1,334 Big Data Tools jobs in Singapore

Overview
OniGroup is a globally recognised Google Cloud Premier Partner, celebrated for consistently demonstrating deployment and support excellence. We were awarded the Global Cloud Location Based Services Partner of the Year in 2018 due to our continued focus on delivering positive business impact to our clients, going beyond being just a technology provider. If you are looking to kickstart your career in the exciting field of Artificial Intelligence and Data at a global organisation that provides a long-term career path, ongoing skills training, and exceptional learning opportunities, then OniGroup is the place for you.
The Opportunity
You will be joining a young and vibrant team of professionals in our Singapore office who have an enthusiasm for creative problem-solving while learning new skills on a daily basis. This is a unique opportunity to work at the intersection of data science and data engineering, transforming raw data into impactful business solutions for some of the most innovative companies across the APAC region. You will gain hands-on experience with cutting-edge AI/ML technologies like Vertex AI, BigQuery, and Generative AI models to solve real-world customer challenges.
Who You Are
This position is open to all graduates with a Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related quantitative field. We are looking for individuals who love to try new things, thrive on responsibility, and want more than just a job—but an opportunity to be part of a fun, dynamic, and forward-thinking team at the forefront of the AI revolution.
What You'll Do
Develop & Deploy AI/ML Solutions:
Assist in the end-to-end lifecycle of machine learning and AI projects, from data ingestion and feature engineering to model training, validation, and deployment on Google Cloud
AI process design:
Assist in designing how AI components can be incorporated into existing workflows or processes
Build Robust Data Pipelines:
Design, build, and maintain scalable and reliable data pipelines using services like Google Cloud Dataflow, Pub/Sub, and BigQuery to process and prepare data for analysis
Data Analysis & Insights:
Perform exploratory data analysis (EDA) to uncover trends, patterns, and insights. Communicate your findings effectively to both technical and non-technical stakeholders
Pre-Sales & Solutioning Support:
Collaborate with senior consultants to understand client needs, contribute to technical discovery sessions, and assist in designing and scoping AI-driven solutions
Client Enablement & Support:
Help prepare and deliver technical workshops and training sessions for customers. Provide post-implementation support to ensure the success and adoption of our solutions
Continuous Learning:
Stay up-to-date with the latest advancements in AI, machine learning, and the rapidly evolving Google Cloud ecosystem
What We're Looking For
A solid foundation in computer science, including data structures, algorithms, and software engineering principles
Foundational knowledge of machine learning concepts (e.g., regression, classification, clustering) and statistics
Excellent communication and interpersonal skills, with a passion for explaining complex technical concepts clearly
A strong interest in client-facing work and consulting
Creative thinking and a structured approach to problem-solving
A keen desire to learn, grow, and take on new challenges
A friendly, outgoing personality with the ability to thrive in a collaborative team environment
Eligibility to work in Singapore
Preferred Qualifications (Nice-to-Haves)
Proficiency in Python and familiarity with data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
Experience with SQL and relational/non-relational database concepts
Hands-on experience with Google Cloud Platform (GCP), particularly services like BigQuery, Vertex AI, Google Cloud Storage, or Dataflow, through internships or personal projects
Familiarity with Linux environments and shell scripting
Experience creating data visualisations using tools like Looker Studio, Tableau, or similar
An understanding of containerisation technologies like Docker
How to Apply
If you are ready to launch your career with a leading Google Cloud Partner, please apply with your CV and a brief cover letter explaining why you are interested in this role. We look forward to hearing from you!
Job Details
Seniority level: Entry level
Employment type: Contract
Job function: Information Technology
#J-18808-Ljbffr

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).

• 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.

• 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).

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).

• 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.

• 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).

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.

• 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.

• 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 Title: Big Data Engineer (Java, Spark, Hadoop)

Location : Singapore

Experience : 7- 12 years

Employment Type : Full-Time

Open to Citizens and SPR only | No Visa sponsorship available

We are looking for a Senior Big Data Engineer with 7–12 years of experience to join our growing data engineering team. The ideal candidate will bring deep expertise in Java , Apache Spark , and Hadoop ecosystems, and have a strong track record of designing and building scalable, high-performance big data solutions. This role is critical to ensuring robust data processing and delivering clean, actionable data for business insights and advanced analytics.

• Design, build, and optimize large-scale, distributed data processing systems using Apache Spark , Hadoop , and Java .
• Lead the development and deployment of data ingestion , ETL/ELT pipelines , and data transformation frameworks .
• Work with cross-functional teams to gather data requirements and translate them into scalable data solutions.
• Ensure high performance and reliability of big data systems through performance tuning and best practices.
• Manage and monitor batch and real-time data pipelines from diverse sources including APIs, databases, and streaming platforms like Kafka .
• Apply deep knowledge of Java to build efficient, modular, and reusable codebases.
• Mentor junior engineers, participate in code reviews, and enforce engineering best practices.
• Collaborate with DevOps teams to build CI/CD pipelines and automate deployment processes.
• Ensure data governance , security , and compliance standards are maintained.

• 7–12 years of experience in big data engineering or backend data systems.
• Strong hands-on programming skills in Java ; exposure to Scala or Python is a plus.
• Proven experience with Apache Spark , Hadoop (HDFS, YARN, MapReduce), and related tools.
• Solid understanding of distributed computing , data partitioning, and optimization techniques.
• Experience with data access and storage layers like Hive , HBase , or Impala .
• Familiarity with data ingestion tools like Apache Kafka , NiFi , Flume , or Sqoop .
• Comfortable working with SQL for querying large datasets.
• Good understanding of data architecture , data modeling , and data lifecycle management .
• Experience with cloud platforms like AWS , Azure , or Google Cloud Platform .
• Strong problem-solving, analytical, and communication skills.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• Experience with streaming data frameworks such as Spark Streaming , Kafka Streams , or Flink .
• Knowledge of DevOps practices , CI/CD pipelines, and infrastructure as code (e.g., Terraform).
• Exposure to containerization (Docker) and orchestration (Kubernetes) .
• Certifications in Big Data technologies or Cloud platforms are a plus.

Please note that this is an equal opportunities employer.

We are seeking a highly skilled and experienced Big Data Engineer to join our team. The ideal candidate will have a minimum of 5 years of experience managing data engineering jobs in big data environment e.g., Cloudera Data Platform. The successful candidate will be responsible for designing, developing, and maintaining the data ingestion and processing jobs. Candidate will also be integrating data sets to provide seamless data access to users.

SKILLS SET AND TRACK RECORD

• Good understanding and completion of projects using waterfall/Agile methodology.
• Analytical, conceptualisation and problem-solving skills.
• Good understanding of analytics and data warehouse implementations
• Hands-on experience in big data engineering jobs using Python, Pyspark, Linux, and ETL tools like Informatica
• Strong SQL and data analysis skills. Hands-on experience in data virtualisation tools like Denodo will be an added advantage
• Hands-on experience in a reporting or visualization tool like SAP BO and Tableau is preferred
• Track record in implementing systems using Cloudera Data Platform will be an added advantage.
• Motivated and self-driven, with ability to learn new concepts and tools in a short period of time
• Passion for automation, standardization, and best practices
• Good presentation skills are preferred

The developer is responsible to:

• Analyse the Client data needs and document the requirements.
• Refine data collection/consumption by migrating data collection to more efficient channels
• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.
• Develop test plan and scripts for system testing, support user acceptance testing.
• Work with the Client technical teams to ensure smooth deployment and adoption of new solution.
• Ensure the smooth operations and service level of IT solutions.
• Support production issues

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