Solution Architect

REGTECH INSIGHT PTE. LTD.; Singapore; In loco; SGD 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

REGTECH INSIGHT PTE. LTD. in Singapore seeks an experienced Data Engineer to design, develop, and maintain scalable data pipelines within an Enterprise Data Lake, leveraging Cloudera CDP, Hadoop, Spark, Hive, Java, Python, and SQL.

The role requires strong stakeholder management, project delivery across BAU and multi-project portfolios, with Banking and Financial Services experience preferred.

Competenze

• Experience designing and delivering large data platforms.
• Strong data modeling and transformation skills required.
• Ability to manage multiple projects and BAU portfolios.

Mansioni

• Design, develop and maintain scalable data pipelines in Enterprise Data Lake.
• Create high-performance batch and near real-time ingestion frameworks.
• Develop transformations using Spark, HiveQL, SQL and Java-based processing.
• Implement ingestion patterns for structured, semi-structured, and unstructured data.
• Build and maintain batch and real-time data integration solutions.
• Define source-to-target mappings and ingestion specs.
• Deploy, troubleshoot, and optimize Hadoop-based apps.
• Collaborate with platform teams for cluster utilization and workload mgmt.
• Provide L3 production support and incident resolution.
• Monitor pipelines, cluster health and performance.

Conoscenze

Data pipelines

Hadoop

Cloudera

Spark

Java

Python

SQL

Unix scripting

Data governance

Strumenti

Git

Jenkins

Azure DevOps

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.