606 Big Data jobs in Singapore

We're looking for a seasoned Big Data Engineering Lead with expertise in Scala, Python, and PySpark to lead our client data engineering team. You'll be responsible for designing and implementing scalable, efficient, and fault-tolerant data pipelines, as well as mentoring team members and driving technical innovation.

Key Responsibilities:

• Design and develop large-scale data pipelines using Scala, Python, and PySpark

• Lead and mentor a team of data engineers to build and maintain data architectures

• Collaborate with cross-functional teams to identify data requirements and implement data-driven solutions

• Ensure data quality, integrity, and security across all data pipelines

• Develop and maintain technical documentation for data pipelines and architectures

• Stay up-to-date with industry trends and emerging technologies in big data, cloud computing, and data engineering

• Drive technical innovation and recommend new tools and technologies to improve data engineering capabilities

Requirements:

• 5+ years of experience in big data engineering, with expertise in Scala, Python, and PySpark

• Strong experience with big data technologies such as Apache Spark, Hadoop, and Kafka

• Experience with cloud-based data platforms such as AWS, GCP, or Azure

• Strong understanding of data architecture, data governance, and data security

• Excellent leadership and mentoring skills, with experience leading high-performing teams

• Strong communication and collaboration skills, with ability to work with cross-functional teams

• Bachelor's or Master's degree in Computer Science, Engineering, or related field

We're looking for a seasoned Big Data Engineering Lead with expertise in Scala, Python, and PySpark to lead our client data engineering team. You'll be responsible for designing and implementing scalable, efficient, and fault-tolerant data pipelines, as well as mentoring team members and driving technical innovation.

Key Responsibilities:

1. Design and develop large-scale data pipelines using Scala, Python, and PySpark
2. Lead and mentor a team of data engineers to build and maintain data architectures
3. Collaborate with cross-functional teams to identify data requirements and implement data-driven solutions
4. Ensure data quality, integrity, and security across all data pipelines
5. Develop and maintain technical documentation for data pipelines and architectures
6. Stay up-to-date with industry trends and emerging technologies in big data, cloud computing, and data engineering
7. Drive technical innovation and recommend new tools and technologies to improve data engineering capabilities

Requirements:

1. 5+ years of experience in big data engineering, with expertise in Scala, Python, and PySpark
2. Strong experience with big data technologies such as Apache Spark, Hadoop, and Kafka
3. Experience with cloud-based data platforms such as AWS, GCP, or Azure
4. Strong understanding of data architecture, data governance, and data security
5. Excellent leadership and mentoring skills, with experience leading high-performing teams
6. Strong communication and collaboration skills, with ability to work with cross-functional teams
7. Bachelor's or Master's degree in Computer Science, Engineering, or related field

We're looking for a seasoned Big Data Engineering Lead with expertise in Scala, Python, and PySpark to lead our client data engineering team. You'll be responsible for designing and implementing scalable, efficient, and fault-tolerant data pipelines, as well as mentoring team members and driving technical innovation.
Key Responsibilities:
Design and develop large-scale data pipelines using Scala, Python, and PySpark
Lead and mentor a team of data engineers to build and maintain data architectures
Collaborate with cross-functional teams to identify data requirements and implement data-driven solutions
Ensure data quality, integrity, and security across all data pipelines
Develop and maintain technical documentation for data pipelines and architectures
Stay up-to-date with industry trends and emerging technologies in big data, cloud computing, and data engineering
Drive technical innovation and recommend new tools and technologies to improve data engineering capabilities
Requirements:
5+ years of experience in big data engineering, with expertise in Scala, Python, and PySpark
Strong experience with big data technologies such as Apache Spark, Hadoop, and Kafka
Experience with cloud-based data platforms such as AWS, GCP, or Azure
Strong understanding of data architecture, data governance, and data security
Excellent leadership and mentoring skills, with experience leading high-performing teams
Strong communication and collaboration skills, with ability to work with cross-functional teams
Bachelor's or Master's degree in Computer Science, Engineering, or related field
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Job Description:

• We are seeking a highly skilled and motivated Big Data Engineer to join our data team. The ideal candidate will play a key role in designing, developing, and maintaining scalable big data solutions while providing technical leadership. This role will also support strategic Data Governance initiatives, ensuring data integrity, privacy, and accessibility across the organization.

Key Responsibilities:

• Design, implement, and optimize robust data pipelines and ETL/ELT workflows using SQL and Python.
• Collaborate closely with Data Engineers, Analysts, and cross-functional engineering teams to meet evolving data needs.
• Build synchronous and asynchronous data APIs for downstream systems to consume the data.
• Deploy and manage infrastructure using Terraform and other
• Infrastructure-as-Code (IaC) tools.
• Develop and maintain CI/CD pipelines for deploying data applications and services.
• Leverage strong experience in AWS services (e.g., S3, Glue, Lambda, RDS, Lake
• Formation) to support scalable and secure cloud-based data platforms.
• Handle both batch and real-time data processing effectively.
• Apply best practices in data modeling and support data privacy and data protection initiatives.
• Implement and manage data encryption and hashing techniques to secure sensitive information.
• Ensure adherence to software engineering best practices including version control, automated testing, and deployment standards.
• Lead performance tuning and troubleshooting for data applications and platforms.

Required Skills & Experience:

• Strong proficiency in SQL for data modeling, querying, and transformation.
• Advanced Python development skills with an emphasis on data engineering use cases.
• Hands-on experience with Terraform for cloud infrastructure provisioning.
• Proficiency with CI/CD tools, particularly GitHub Actions.
• Deep expertise in AWS cloud architecture and services.
• Demonstrated ability to create and evaluate ERDs and contribute to architectural decisions.
• Strong communication.

Preferred Qualifications:

• Experience with big data technologies such as Apache Spark, Hive, or Kafka.
• Familiarity with containerization tools (e.g., Docker) and orchestration platforms (e.g., Kubernetes) .
• Solid understanding of data governance, data quality, and security frameworks.

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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
  
  

• 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

• Seniority level Mid-Senior level

• Employment type Contract

• Job function Information Technology
• Industries IT Services and IT Consulting

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South East Community Development Council, Singapore 1 week ago

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Job Responsibility:

• Work with data science team to complete game data analysis, including data logic combing, basic data processing, analysis and corresponding development work.
• Complete basic data analysis, machine learning analysis, and build the required data processing flow, data report visualization.
• Develop data processing pipelines for data modelling, analysis, and reporting from large and complex transaction datasets
• Ability to assist in supporting engineering development, data construction and maintenance when required.

Requirements:

• Degree in Computer Science or related technical field
• At least 2 years of experience in data analysis/data warehouse/mart development and BI reporting.
• At least 2 years of experience in ETL processing data.
• Good understanding of Python, SQL, HiveQL/SparkSQL and the relevant best practices/techniques for perf tuning, experience deploying models in production and adjusting model thresholds to improve performance is a plus.
• Familiarity with data visualization tools, such as Google Analytics or Tableau.

• We are seeking a highly skilled and motivated Big Data Engineer to join our data team. The ideal candidate will play a key role in designing, developing, and maintaining scalable big data solutions while providing technical leadership. This role will also support strategic Data Governance initiatives, ensuring data integrity, privacy, and accessibility across the organization.

• Design, implement, and optimize robust data pipelines and ETL/ELT workflows using SQL and Python.
• Collaborate closely with Data Engineers, Analysts, and cross-functional engineering teams to meet evolving data needs.
• Build synchronous and asynchronous data APIs for downstream systems to consume the data.
• Deploy and manage infrastructure using Terraform and other
• Infrastructure-as-Code (IaC) tools.
• Develop and maintain CI/CD pipelines for deploying data applications and services.
• Leverage strong experience in AWS services (e.g., S3, Glue, Lambda, RDS, Lake
• Formation) to support scalable and secure cloud-based data platforms.
• Handle both batch and real-time data processing effectively.
• Apply best practices in data modeling and support data privacy and data protection initiatives.
• Implement and manage data encryption and hashing techniques to secure sensitive information.
• Ensure adherence to software engineering best practices including version control, automated testing, and deployment standards.
• Lead performance tuning and troubleshooting for data applications and platforms.

• Strong proficiency in SQL for data modeling, querying, and transformation.
• Advanced Python development skills with an emphasis on data engineering use cases.
• Hands-on experience with Terraform for cloud infrastructure provisioning.
• Proficiency with CI/CD tools, particularly GitHub Actions.
• Deep expertise in AWS cloud architecture and services.
• Demonstrated ability to create and evaluate ERDs and contribute to architectural decisions.
• Strong communication.

• Experience with big data technologies such as Apache Spark, Hive, or Kafka.
• Familiarity with containerization tools (e.g., Docker) and orchestration platforms (e.g., Kubernetes) .
• Solid understanding of data governance, data quality, and security frameworks.