Solution Architect

JEET ANALYTICS PTE. LTD.; Singapore; In loco; SGD 180.000 - 240.000; Tempo pieno

Descrizione del lavoro

JEET ANALYTICS PTE. LTD. in Singapore seeks a senior Data Engineer to lead enterprise data lake and warehouse initiatives for the banking and financial services sector.

The role requires deep knowledge of Hadoop/Cloudera, Spark, Hive, Java, Python, and SQL, plus strong stakeholder management and delivery of complex programs. You will design scalable pipelines, implement real-time ingestion, ensure data quality and governance, and support production systems while collaborating with platform teams

Competenze

• 10+ years of experience in data engineering or related roles.
• Strong stakeholder management and ability to deliver complex projects.

Mansioni

• Design, develop, and maintain scalable pipelines in Enterprise Data Lake/warehouse.
• Ingest, transform, and govern data using Spark, Hive, SQL, Java, and Python.
• Ensure data quality, governance, and incident handling across production stacks.
• Collaborate with platform teams for CI/CD, deployment, and performance tuning.
• Provide L3 production support and optimize cluster utilization.

Conoscenze

Hadoop/Cloudera

Spark

Hive

Java

Python

SQL

Data Lake

Data Warehousing

ETL/ELT

Data Governance

Stakeholder Management

Project Delivery

Production Support

Strumenti

Cloudera CDP

Hadoop HDFS

Kafka

YARN/Oozie

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.