Analytics Engineer

About the role

Workato is actively hiring an Analytics Engineer to join their growing team based in Singapore. This role focuses on building and maintaining data infrastructure that supports business intelligence and decision-making across the organization. The Analytics Engineer will work closely with cross-functional teams to transform raw data into actionable insights and drive strategic outcomes. Candidates should be comfortable working in a fast-paced environment where data quality, reliability, and collaboration are top priorities.

Key facts

What you'll do

• Design, build, and maintain scalable, reliable data pipelines that move information between various source systems and analytical platforms.
• Build and optimize interactive dashboards and reports that help stakeholders monitor key business metrics and KPIs.
• Collaborate with engineering teams to ensure data models are well-structured, properly documented, and easy to understand.
• Write and maintain complex SQL queries to extract, transform, and load data for reporting and analytical purposes.
• Develop comprehensive automated testing procedures to validate data accuracy, consistency, and integrity across all datasets.
• Partner with product and operations teams to understand their analytical needs and deliver scalable, reliable solutions.
• Monitor data quality and troubleshoot issues that arise in downstream analytics and reporting.
• Create and maintain comprehensive documentation describing data definitions, transformations, pipeline architectures, and operational runbooks.
• Participate in code reviews, mentor junior team members, and contribute to best practices for data engineering workflows.
• Support the adoption of analytics tools and platforms across different departments within the organization.
• Evaluate new data sources and assess their suitability for integration into existing analytics workflows.
• Contribute to the development of data standards and governance policies across the analytics organization.
• Identify opportunities for process automation and efficiency improvements within the data engineering lifecycle.
• Conduct research on emerging data technologies and recommend tools that can enhance the analytics stack.

Requirements

• A Bachelor's degree in computer science, engineering, mathematics, or a related quantitative discipline is required for this position.
• Strong proficiency in SQL and hands-on experience working with relational databases at scale in production environments.
• Experience building and managing data pipelines using modern data integration and transformation tools within production environments.
• Familiarity with data modeling techniques, dimensional modeling, and schema design best practices.
• Ability to write clean, well-documented, maintainable code and follow version control workflows consistently across all projects.
• Understanding of data governance principles, data quality assurance, and compliance methodologies.
• Experience working with business intelligence and data visualization platforms to deliver actionable insights.
• Strong analytical thinking and the ability to communicate technical concepts to non-technical stakeholders.
• Experience with data warehousing concepts and familiarity with OLAP cubes or similar structures.
• Strong written and verbal communication skills with the ability to present findings clearly.
• Experience with version control systems, CI/CD pipelines, and automated testing frameworks for data applications.

Nice to have

• Experience with cloud-based data warehouses and large-scale big data processing frameworks such as Apache Spark or Hadoop.
• Knowledge of Python or another general-purpose programming language for data manipulation, scripting, and automation tasks.
• Familiarity with workflow orchestration tools and scheduling systems for automated data pipelines.
• Exposure to machine learning concepts and the ability to support ML-driven analytics initiatives.
• Experience working in an agile development environment with iterative delivery cycles and cross-functional collaboration.
• Strong understanding of statistical concepts and the ability to apply them to business problems.

Skills & tools

• SQL and relational database management systems for efficient data storage, retrieval, and manipulation
• Data pipeline design, ETL processes, and data transformation workflows
• Business intelligence platforms and data visualization reporting tools for stakeholder consumption
• Data modeling, dimensional modeling, and schema design principles
• Version control systems such as Git for collaborative development
• Cloud computing platforms and distributed data storage services
• Data validation, quality checking frameworks, and reconciliation procedures
• API integration and RESTful service consumption
• Data governance frameworks and metadata management practices

Practical notes

• This full-time position is based in Singapore and requires regular on-site presence at the Workato office.
• The hiring process includes multiple rounds of technical assessments, coding challenges, and behavioral interviews.
• Candidates should be prepared to discuss past projects involving data infrastructure, analytics solutions, and cross-team collaboration.
• Workato deeply values diversity and inclusion and warmly encourages applicants from all backgrounds and experiences to apply.
• Employees at Workato benefit from a supportive, inclusive culture that emphasizes continuous learning, professional growth, and team collaboration.
• The company offers competitive benefits and a collaborative workspace that supports professional development.