System Analyst – Data | TechEdge Solution | Singapore

TechEdge Solution; Singapore; On-site; SGD 140,000 - 210,000; Full time

Job summary

TechEdge Solution in Singapore is seeking an experienced System Analyst – Data to design and govern enterprise data platforms that support analytics, regulatory reporting, and AI-enabled use cases across retail banking. You will lead data architectures across the full SDLC to deliver scalable, compliant solutions.

The role requires 8–12 years in modern data architectures, hands-on Python/SQL, and experience with Databricks, Snowflake, BigQuery, and Spark.

Qualifications

• 8–12 years of experience in data analysis, data architecture, or enterprise platform engineering.
• Expertise in enterprise data and analytics across structured and unstructured data.
• Experience with NLP, machine learning, statistical analytics, knowledge graphs, and decision support systems.
• Strong mastery of modern data architectures spanning batch, micro-batch, and real-time processing paradigms.
• Comprehensive knowledge of data governance, lineage, quality control, and regulatory compliance in financial services.
• Extensive technical proficiency in modern data stacks including Databricks, Snowflake, Azure Fabric, BigQuery, and Spark.
• Advanced coding and querying skills in Python, SQL, and BTEQ.
• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline.

Responsibilities

• Design and govern enterprise data platforms handling structured and unstructured data for retail banking and financial services.
• Lead end-to-end solution delivery across the full SDLC for scalable data and analytics implementations.
• Translate complex business and regulatory requirements into robust, scalable technical system designs.
• Communicate technical concepts, data strategies, and architecture decisions clearly to executive stakeholders.
• Manage operational risks, ensure data quality, and maintain compliance with regulatory commitments and timelines.
• Drive innovation, data cataloging, governance, and AI enablement across enterprise data operations.
• Design specialized data architectures for NLP, machine learning, and unstructured data.
• Partner with internal support teams to execute root-cause analysis and resolve performance bottlenecks swiftly.

Skills

Data architecture

NLP

Machine learning

Python

SQL

Governance

Regulatory compliance

Data quality

Education

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline

Master’s degree in Data Science, Computer Science, or quantitative engineering field

Tools

Databricks

Snowflake

Azure Fabric

BigQuery

Spark

Job description

Position Summary:

TechEdge Solution is seeking an experienced and results-driven System Analyst – Data to join our technology team in Singapore on a full-time basis. In this pivotal role, you will be responsible for designing and governing enterprise data platforms that handle structured and unstructured data, supporting advanced analytics, regulatory reporting, and AI-enabled use cases. You will collaborate across the full software development life cycle (SDLC) to deliver scalable, compliant, and high-quality data and analytics solutions tailored for retail banking and financial services. This opportunity requires a seasoned data professional with 8 to 12 years of experience in modern data architecture and enterprise data platforms.

Detailed Job Description:

As a System Analyst – Data, you will take full ownership of designing enterprise data architectures, leading solution delivery across the complete SDLC, and translating complex business and regulatory requirements into scalable technical designs. Your day-to-day responsibilities include partnering with support teams for root-cause analysis, collaborating on machine learning and rule-based decision systems, and evaluating advanced data and AI tools through RFPs and PoCs. You will work across advanced data platforms including Databricks, Snowflake, Azure Fabric, and BigQuery, ensuring robust data governance, lineage, quality, and regulatory compliance. Furthermore, you will drive innovation, streamline data cataloging, and improve operational efficiency across analytics delivery pipelines in regulated financial environments.

Key Responsibilities:

• Design and govern enterprise data platforms handling structured and unstructured data for retail banking and financial services.
• Lead end-to-end solution delivery across the full SDLC for scalable data and analytics implementations.
• Translate complex business and regulatory requirements into robust, scalable technical system designs.
• Communicate technical concepts, data strategies, and architecture decisions clearly to executive stakeholders.
• Manage operational risks, ensure data quality, and maintain compliance with regulatory commitments and timelines.
• Drive innovation, data cataloging, governance, and AI enablement across enterprise data operations.
• Design specialized data architectures for Natural Language Processing (NLP), machine learning, and unstructured data.
• Partner with internal support teams to execute root-cause analysis and resolve performance bottlenecks swiftly.

Required Qualifications & Skills:

• Minimum of 8 to 12 years of professional experience in data analysis, data architecture, or enterprise platform engineering.
• Deep expertise in enterprise data and analytics across structured and unstructured data environments.
• Proven practical experience in NLP, machine learning, statistical analytics, knowledge graphs, and decision support systems.
• Strong mastery of modern data architectures spanning batch, micro-batch, and real-time processing paradigms.
• Comprehensive knowledge of data governance, lineage, quality control, and regulatory compliance in financial services.
• Extensive technical proficiency in modern data stacks including Databricks, Snowflake, Azure Fabric, BigQuery, and Spark.
• Advanced coding and querying skills in Python, SQL, and BTEQ.
• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline.

Nice-to-Have Skills:

• Master’s degree in Data Science, Computer Science, or a quantitative engineering field.
• Professional certifications in cloud data platforms (e.g., Databricks Certified Associate, Snowflake SnowPro Core).
• Prior working experience within retail banking, credit risk analytics, or regulated financial services institutions.
• Experience utilizing enterprise business intelligence and data integration tools such as Power BI, QlikSense, and Informatica.
• Familiarity with distributed search and processing frameworks such as Trino, Presto, and Hive.

Recruitment Pro Tip:

When applying for this System Analyst – Data role, ensure your resume explicitly highlights your hands‑on experience with enterprise data platforms like Databricks and Snowflake, as well as your expertise in financial services data governance and credit risk analytics.