APPLICATION DEVELOPMENT MANAGER

JEET ANALYTICS PTE. LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

JEET ANALYTICS PTE. LTD.

in Singapore seeks an experienced Data Engineering Lead to steer teams in designing scalable enterprise data platforms and pipelines, aligning technical delivery with business goals. You will mentor engineers, drive hands-on development with Hadoop, Spark, PySpark, Hive, Kafka, and cloud data platforms, and collaborate with stakeholders to translate requirements into robust data solutions.

Qualifications

• 10+ years of experience in data engineering, Big Data development, and enterprise data platforms.
• Strong proficiency in Python, PySpark, SQL, and distributed data processing frameworks.
• Proven hands‑on expertise in Big Data technologies with ability to guide teams technically and troubleshoot complex challenges.
• Experience building and managing complex data pipelines, ETL/ELT workflows, and large-scale data processing solutions.
• Demonstrated leadership in managing data engineering teams, deliverables, and driving technical execution.

Responsibilities

• Lead data engineering teams to design, develop, and deliver scalable enterprise data platforms and pipelines that meet business needs
• Maintain hands-on expertise in Big Data technologies including Hadoop, Spark, PySpark, Hive, Kafka, and distributed data processing to solve complex engineering challenges
• Design and implement robust ETL/ELT pipelines, data ingestion frameworks, data transformation, and integration solutions for large-scale data processing
• Drive data engineering architecture, perform technical design, and optimize performance of data workloads to ensure scalability and efficiency
• Manage implementations of data lakes, data warehouses, and modern cloud-based data platforms to support enterprise data needs
• Utilize cloud platforms such as AWS, Azure, or GCP and technologies like Databricks to build and maintain data engineering solutions
• Lead initiatives on data quality, data governance, metadata management, security, and data reliability to uphold enterprise standards
• Collaborate with solution architects, data architects, business stakeholders, and project managers to translate business requirements into technical solutions
• Manage project delivery including resource allocation, technical reviews, risk mitigation, and adherence to delivery timelines
• Mentor engineers by establishing best practices and ensuring delivery of high-quality, maintainable, and production-ready code

Skills

Big Data

Leadership

Stakeholder management

Problem solving

Mentoring

Tools

Python

PySpark

SQL

Hadoop

Spark

Hive

Kafka

Databricks

AWS

Azure

GCP

Job description

Job Summary

Lead and manage data engineering teams to design and deliver scalable enterprise data platforms and pipelines, driving technical execution and collaboration with stakeholders to meet business requirements.

Responsibilities

• Lead data engineering teams to design, develop, and deliver scalable enterprise data platforms and pipelines that meet business needs
• Maintain hands-on expertise in Big Data technologies including Hadoop, Spark, PySpark, Hive, Kafka, and distributed data processing to solve complex engineering challenges
• Design and implement robust ETL/ELT pipelines, data ingestion frameworks, data transformation, and integration solutions for large-scale data processing
• Drive data engineering architecture, perform technical design, and optimize performance of data workloads to ensure scalability and efficiency
• Manage implementations of data lakes, data warehouses, and modern cloud-based data platforms to support enterprise data needs
• Utilize cloud platforms such as AWS, Azure, or GCP and technologies like Databricks to build and maintain data engineering solutions
• Lead initiatives on data quality, data governance, metadata management, security, and data reliability to uphold enterprise standards
• Collaborate with solution architects, data architects, business stakeholders, and project managers to translate business requirements into technical solutions
• Manage project delivery including resource allocation, technical reviews, risk mitigation, and adherence to delivery timelines
• Mentor engineers by establishing best practices and ensuring delivery of high-quality, maintainable, and production-ready code

Required competencies and certifications

• 10+ years of experience in data engineering, Big Data development, and enterprise data platforms
• Proven hands‑on expertise in Big Data technologies with ability to guide teams technically and troubleshoot complex challenges
• Strong proficiency in Python, PySpark, SQL, and distributed data processing frameworks
• Experience building and managing complex data pipelines, ETL/ELT workflows, and large-scale data processing solutions
• Demonstrated leadership in managing data engineering teams, deliverables, and driving technical execution
• Strong understanding of data modelling, data architecture, performance optimization, and platform scalability
• Excellent stakeholder management, communication, problem-solving, and leadership skills

Preferred competencies and qualifications

• Experience with cloud-based data engineering and modern data platforms
• Background in banking, financial services, regulatory reporting, risk analytics, or other data-intensive enterprise environments