Solution Architect

Riskdata Consulting; Singapore; In loco; SGD 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

Riskdata Consulting is seeking a senior data engineer to design, develop, and operate enterprise data pipelines within a Banking/Financial Services context. You will work across Data Lake, Data Warehouse, and big data initiatives, leveraging Hadoop, Cloudera CDP, Spark, Hive, Kafka, and Java/Python to deliver scalable solutions.

This role requires strong stakeholder management and the ability to manage multiple deliveries and BAU portfolios while ensuring governance and quality across data

Competenze

• 10+ years of experience in data engineering or related roles.
• 5+ years delivering Enterprise Data Lake, Data Warehouse or Big Data initiatives.
• Proven experience in Hadoop/Cloudera environments.
• Experience managing multiple concurrent project deliveries and BAU portfolios.
• Banking and Financial Services experience preferred.

Mansioni

• Design and maintain scalable data pipelines on the Data Lake platform.
• Develop high-performance batch and near real-time ingestion frameworks.
• Implement data transformations using Spark, HiveQL, SQL, and Java.
• Ensure data ingestion supports structured, semi-structured, and unstructured data.
• Provide L3 production support and incident management for Data Lake apps.

Conoscenze

Stakeholder management

Project delivery

Data modeling

Communication

Team leadership

Strumenti

Hadoop

Cloudera CDP

Hive

Spark

Kafka

YARN

Oozie

HDFS

Java

Python

SQL

Unix/Linux scripting

Shell scripting

ETL/ELT

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.