Solution Architect

UARROW PTE. LTD.; Singapore; In loco; SGD 154.000 - 231.000; Tempo pieno

Descrizione del lavoro

UARROW PTE. LTD. seeks an experienced Data Engineer to design, develop and operate scalable data pipelines in a Data Lake environment. You will leverage Cloudera CDP, Hadoop, Spark, Hive, Java, Python and SQL to ingest and transform large enterprise data, while ensuring governance and quality across platforms.

You will own end-to-end delivery, manage multiple concurrent projects, and collaborate with stakeholders in a banking/financial services context to optimize performance and reliability.

Competenze

• 10+ years of experience in enterprise data platforms.
• 5+ years managing Enterprise Data Lake, Data Warehouse or Big Data projects.
• Proven experience in Hadoop/Cloudera environments.
• Banking/financial services experience preferred.
• Experience managing multiple concurrent project deliveries and BAU portfolios.
• Strong stakeholder management and communications.

Mansioni

• Design, develop, and maintain scalable data pipelines in the data lake using Cloudera CDP, Hadoop, Spark, Hive, Java, Python, and SQL.
• Develop high-performance batch and near real-time data ingestion frameworks for onboarding enterprise source systems into the Data Lake.
• Develop complex transformation logic using Spark, HiveQL, SQL, and Java-based processing frameworks.
• Design and implement data ingestion patterns for structured, semi-structured, and unstructured datasets.
• Build and maintain batch and near real-time data integration solutions.
• Implement source-to-target mappings and ingestion specifications.
• Perform deployment, troubleshooting, and performance tuning of Hadoop applications.
• Partner with platform teams to ensure optimal cluster utilization and workload management.
• Provide L3 production support; monitor pipelines and incident management.
• Data quality, governance, and compliance with standards.

Conoscenze

Enterprise data platforms

Stakeholder management

Project delivery

SQL development

Java

Python

Data modeling

Data integration

Big data concepts

Strumenti

Hadoop

Cloudera CDP

Spark

Hive

Kafka

YARN

Oozie

Git

Jenkins

Azure DevOps

Unix/Linux scripting

Shell scripting

Descrizione del lavoro

This role requires strong technical knowledge of enterprise data platforms, excellent stakeholder management skills, and proven experience delivering complex projects within the banking and financial services industry.

10+ years of experience.

5+ years managing Enterprise Data Lake, Data Warehouse or Big Data delivery initiatives.

Proven experience in Hadoop/Cloudera environments.

Experience managing multiple concurrent project deliveries and BAU portfolios.

Banking and Financial Services experience preferred.

Data Engineering & Integration

• Design, develop, and maintain scalable data pipelines within the Enterprise Data Lake platform using Cloudera CDP, Hadoop, Spark, Hive, Java, Python, and SQL.
• Develop high-performance batch and near real-time data ingestion frameworks for onboarding enterprise source systems into the Data Lake.
• Develop complex transformation logic using Spark, HiveQL, SQL, and Java-based processing frameworks.
• Design and implement data ingestion patterns supporting structured, semi-structured, and unstructured datasets.
• Build and maintain batch and near real-time data integration solutions.
• Implement source-to-target mappings and ingestion specifications.

Hadoop & Cloudera Platform Development

• Develop and support solutions within the Cloudera Data Platform ecosystem.
• Build and maintain data pipelines leveraging:
• Hadoop HDFS
• Hive
• Impala
• Spark
• Kafka
• YARN, Oozie
• Perform deployment, troubleshooting, and performance tuning of applications running on the Hadoop ecosystem.
• Partner with platform teams to ensure optimal cluster utilization and workload management.

Data Quality & Governance

• Ensure adherence to Data Lake onboarding standards and governance requirements.
• Investigate and resolve data quality issues and production incidents.
• Ensure compliance with enterprise data governance standards.

DevOps & Platform Automation

• Integrate data engineering solutions into CI/CD pipelines using Git, Jenkins, Azure DevOps, or equivalent tools.
• Automate deployment, testing, monitoring, and operational support activities.
• Develop reusable frameworks and utilities to improve engineering productivity and platform scalability.

Production Support & Incident Management

• Provide L3 support for Data Lake application.
• Perform root cause analysis for production incidents and implement permanent fixes.
• Monitor pipeline execution, cluster health, and workload performance.
• Participate in release implementation, deployment validation, and post-production support activities.
• Strong hands on experience with Hadoop ecosystem and data pipeline orchestration.
• Hadoop/HDFS
• Hive
• Spark
• Unix/Linux scripting
• Shell scripting
• ETL/ELT development experience.
• Data modelling fundamentals.
• Performance tuning and optimization.
• Experience in Data Warehousing and Data Lake environments.
• Strong Java / Python competency with experiences.
• Strong SQL development skills.