Top Data Engineer Jobs in Singapore

The Data Engineer II is responsible for ensuring accurate and pertinent data for the Legal and Compliance departments. They extract and analyze data from multiple databases/platforms, design analytics models, and address business challenges. The role involves ensuring data integrity, conducting root-cause analyses, and implementing corrective measures for data-related issues.

Responsible for collecting, designing, storing, and processing payments data in eCommerce business. Leading role in constructing business evaluation metrics, developing data services tactics, and creating data-driven tools. Defining business data requirements and building models to enhance data quality and stability.

Design, develop, and maintain real-time and batch data processing pipelines using Apache Flink, collaborate with cross-functional teams, troubleshoot and resolve performance bottlenecks in stream processing, and improve system performance and data integrity.

Design, build, and manage data pipelines using Apache Spark and Scala. Utilize Google Cloud Platform for large-scale data processing systems. Analyze complex data sets and implement internal process improvements. Provide technical leadership and coaching to junior team members.

Develop high performance and scalable solutions to extract, transform, and load big data at Walmart Global Tech. Support People Data applications, ensuring data quality and governance standards. Collaborate with engineering teams to drive value from data at Walmart Scale.

Build and optimize 'big data' data pipelines, perform root cause analysis, support data modeling, manipulate large datasets, work with message queuing and stream processing, and perform CI/CD activities.

Seeking a Data Engineer to design, develop, and maintain data solutions for analytics and business purposes. Responsibilities include data integration, processing, retrieval, and transformation to enable valuable insights for decision-making. The role requires collaboration with cross-functional teams to enhance data solutions leveraging modern tech stack.

Design and build resilient data pipelines, architect cloud data infrastructure, collaborate with cross-functional teams, ensure data integrity and scalability, and drive continuous improvement of products and services in a fast-paced environment.

Facilitates implementation of enhancements to business analytics solutions, performs data mining with large datasets, validates data quality and transformation, ensures data integrity, analyzes trends in complex datasets, collaborates with various teams, and provides impact analysis of operational policies. Requires Bachelor's degree and 2+ years of relevant experience in healthcare data analytics or data engineering.

Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data, Integrate Elasticsearch with Spark for efficient indexing and querying, Optimize and tune Spark jobs for performance and scalability, Collaborate with stakeholders to translate requirements into technical solutions, Implement data transformations and aggregations using Spark RDDs, DataFrames, and Datasets, Develop and maintain scalable Spark applications following best practices, Troubleshoot and resolve data processing issues in Spark-Elasticsearch integration

Looking for a Senior Data Engineer to create and manage data infrastructure and tools, evaluate optimal design for data stream, storage, and processing, integrate data platform with application frameworks, support exploration of new technology, and provide technical advice on IT and OT solutions.

Lead and drive the execution of multiple business plans and projects related to data engineering. Implement new architectural patterns and promote high standards of code quality and system reliability. Must have strong hands-on experience with Hadoop, Hive, Apache Spark, and expertise in cloud computing platforms such as Google Cloud Platform (GCP).

Lead Data Engineer responsible for designing, building, and optimizing data infrastructure for advanced analytics needs of the bank. Oversee a team of data engineers and collaborate with stakeholders to deliver high-quality data solutions. Key responsibilities include designing data processing pipelines, optimizing Spark jobs, integrating Elasticsearch, and deploying solutions on OpenShift Container Platform. Must have 10 years of experience as a Data Engineer, Quantexa certification, and proficiency in Hadoop, Spark, and related tools.

The Analyst / Sr Analyst - Data Engineer role at Lilly involves designing, developing, and maintaining complex data solutions for analytics and reporting. The role focuses on ensuring data availability and quality for external government and regulatory reporting purposes. Data engineers play a crucial role in transforming raw data into analysis-ready datasets for decision-making.

Lead Data Engineer responsible for overseeing the development, testing, deployment, and support of large-scale data warehouse systems. Must have experience in data warehousing, data modelling, big data concepts, and proficiency in Python, Scala, or SQL. Experience with frameworks like Spark, Airflow, Hive, Flink, and Kafka, as well as developing data solutions using AWS.

Lead Data Engineer responsible for spearheading the design and enhancement of data warehouse systems, collaborating with stakeholders, leading a team of data engineers, and promoting organization-wide visibility through data insights. Must have at least 6-7 years of experience in Data Warehousing and proficiency in Python, Scala, SQL, and Big Data frameworks.

Design, develop, and optimize Spark Scala applications and data processing pipelines integrated with Elasticsearch. Collaborate with stakeholders, troubleshoot issues, and stay updated on big data technologies trends.