93 Data Engineering Manager jobs in Singapore

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

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).

• Design, implement, and manage big data platforms built on Hadoop, Spark, and Hive.

• Develop and optimize data ingestion, transformation, and storage frameworks for high-volume, high-velocity datasets.

• Maintain and fine-tune Hadoop clusters (HDFS, YARN) including capacity planning, monitoring, and troubleshooting.

• Build and support Hive-based data warehouses for analytics, including schema design, partitioning, and performance optimization.

• Optimize Spark jobs for batch and streaming use cases (memory management, shuffle tuning, query optimization).

• Implement data security and governance policies (Kerberos, Ranger, Atlas) to ensure compliance and controlled access.

• Collaborate with data engineers, architects, and analysts to deliver robust and efficient platform capabilities.

• Drive automation in cluster operations, deployments, and monitoring using scripting and DevOps tools.

Skills

• Experience in data engineering or platform engineering with strong focus on big data ecosystems.

• Deep expertise in Hadoop (HDFS, YARN) cluster management and optimization.

• Strong hands-on experience in Spark (batch + streaming) and Hive data modeling.

• Experience in performance tuning, query optimization, and cluster troubleshooting.

• Familiarity with distributed system internals, resource management, and fault tolerance.

• Knowledge of cloud big data platforms (AWS EMR, Azure HDInsight, GCP Dataproc) is a plus.

• Exposure to automation frameworks (Ansible, Terraform, Airflow, CI/CD pipelines) is preferred.

We are hiring Platform Engineer – Big Data (Hadoop / Spark / Hive) with below requirements;

Responsibilities

• Design, implement, and manage big data platforms built on Hadoop, Spark, and Hive.
• Develop and optimize data ingestion, transformation, and storage frameworks for high-volume, high-velocity datasets.
• Maintain and fine-tune Hadoop clusters (HDFS, YARN) including capacity planning, monitoring, and troubleshooting.
• Build and support Hive-based data warehouses for analytics, including schema design, partitioning, and performance optimization.
• Optimize Spark jobs for batch and streaming use cases (memory management, shuffle tuning, query optimization).
• Implement data security and governance policies (Kerberos, Ranger, Atlas) to ensure compliance and controlled access.
• Collaborate with data engineers, architects, and analysts to deliver robust and efficient platform capabilities.
• Drive automation in cluster operations, deployments, and monitoring using scripting and DevOps tools.

Skills

• Experience in data engineering or platform engineering with strong focus on big data ecosystems.
• Deep expertise in Hadoop (HDFS, YARN) cluster management and optimization.
• Strong hands-on experience in Spark (batch + streaming) and Hive data modeling.
• Experience in performance tuning, query optimization, and cluster troubleshooting.
• Familiarity with distributed system internals, resource management, and fault tolerance.
• Knowledge of cloud big data platforms (AWS EMR, Azure HDInsight, GCP Dataproc) is a plus.
• Exposure to automation frameworks (Ansible, Terraform, Airflow, CI/CD pipelines) is preferred.

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