Analytics Engineer

Posted 6 Days Ago
Be an Early Applicant
Singapore, SGP
In-Office
Junior
Cloud • Enterprise Web • Information Technology • Productivity • Software
Workato helps companies integrate anything and automate everything.
The Role
Own the end-to-end development of reliable data products and scalable dbt models. Build and optimize data warehouse transformations, enforce testing and data quality, monitor pipelines, document data definitions, and collaborate with engineers, analysts, and business stakeholders. Translate analytical needs into production-ready models and champion data usage across the organization. Research and prototype emerging technologies such as GenAI to improve data engineering, orchestration, and product analytics capabilities.
Summary Generated by Built In
About Workato

Workato is the leading Control and Execution Platform for Enterprise AI — the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 — including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors — Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer. For more information, visit workato.com.

Why join us?

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. 

But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. 

If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Also, feel free to check out why:

  • Business Insider named us an “enterprise startup to bet your career on”
  • Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
  • Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
  • Quartz ranked us the #1 best company for remote workers
Responsibilities

As an Analytics Engineer in the Product Management team, you will own the end-to-end delivery of robust, high-quality data products. You will be responsible for designing, developing, maintaining, and scaling mission-critical data models to provide reliable and accessible product usage data, proactively partnering with Data Engineers, Product Analysts, and business stakeholders. Your key mandate is to transform raw data into actionable insights that directly drive strategic product and business decisions, with a continuous focus on technical excellence and platform optimization.

In this role, you will also be responsible to:

  • DBT Modeling & Scalability:

    • Design, develop, and own scalable and maintainable data models using dbt (Data Build Tool), ensuring accurate, intuitive, and consistent data for all end users and stakeholders.

    • Collaborate actively with Data Analysts and Business Stakeholders to translate complex reporting and analysis needs into production-ready, highly optimized dbt models.

    • Enforce and evolve our internal dbt conventions and best practices, continuously optimizing the codebase for cleanliness, performance, and cost-efficiency.

  • Data Reliability and Quality Assurance:

    • Own and enforce data quality and consistency by implementing robust testing, validation, and cleaning processes on mission-critical source tables.

    • Implement and manage data monitoring and alerting solutions to ensure data flows and transformations are performing optimally and accurately, and proactively resolve data anomalies and pipeline failures.

    • Create and maintain comprehensive data documentation and definitions (data dictionaries, process flows) to ensure data literacy, trust, and discoverability for stakeholders

  • Stakeholder Collaboration & Data Enablement:

    • Partner with data engineers, product analysts, GTM data teams, and other stakeholders to strategically align data insights with product improvements and business objectives.

    • Communicate complex data architecture, patterns, and analytical conclusions effectively to both technical and non-technical audiences, driving consensus and action.

    • Act as a data champion, evangelizing and guiding business users on the most efficient and reliable ways to leverage our data products, accelerating their time to insights

  • Emerging Technology & Platform Innovation:

    • Lead the research and evaluation of new tools and technologies, like GenAI, for enhancing data engineering, orchestration, and analysis workflows.

    • Develop and test high-impact prototypes that demonstrate the potential of emerging technologies (e.g., GenAI) to augment and improve our product usage datasets and data platform capabilities.

RequirementsQualifications / Experience / Technical Skills
  • 2+ years of experience in an Analytics Engineering or Data Warehousing role.

  • Expert proficiency in SQL, including advanced techniques like window functions and proven ability in query performance optimization.

  • Demonstrated expertise in dbt (Data Build Tool) for designing, developing, and maintaining complex data models, coupled with strong functional knowledge of a modern cloud data warehouse (e.g., Snowflake, BigQuery).

  • Proven ability to apply data engineering best practices, including version control (Git/GitHub), modular coding, and automated testing, to maintain robust and reliable data pipelines.

  • Strong understanding of data modeling principles (e.g., star/snowflake schemas, Slowly Changing Dimensions) and how to apply them to solve analytical business problems.

  • Proficiency in Python or another scripting language is required.

  • Experience with data orchestration tools (e.g., Airflow, Dagster) for building and managing data workflows.

Soft Skills / Personal Characteristics
  • Resourceful, results-oriented, and autonomous, with a proven track record of owning the full lifecycle of analytical projects from ambiguous requirements to final delivery and business impact.

  • Excellent verbal and written communication and stakeholder management skills, with the ability to translate complex data logic for non-technical audiences and effectively drive cross-functional alignment.

(REQ ID: 2867)

Skills Required

  • 2+ years of experience in analytics engineering or data warehousing
  • Expert proficiency in SQL, including window functions and query performance optimization
  • Expertise with dbt for designing, developing, and maintaining complex data models
  • Functional knowledge of a modern cloud data warehouse such as Snowflake or BigQuery
  • Experience applying data engineering best practices, including Git/GitHub, modular coding, and automated testing
  • Strong understanding of data modeling principles, including star schemas, snowflake schemas, and Slowly Changing Dimensions
  • Proficiency in Python or another scripting language
  • Experience with data orchestration tools such as Airflow or Dagster
  • Ability to own analytical projects from ambiguous requirements through delivery and business impact
  • Excellent verbal and written communication skills
  • Stakeholder management and cross-functional alignment skills

Workato Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Workato and has not been reviewed or approved by Workato.

  • Healthcare Strength — Health insurance is highlighted as robust, with comprehensive medical, dental, vision, and mental health/EAP support. Employer materials and public benefit listings position healthcare as a standout element of the package.
  • Leave & Time Off Breadth — Time off is portrayed as generous, featuring unlimited or flexible PTO in some regions and monthly global days off in addition to holidays. These programs signal a recharge-friendly approach to work-life balance.
  • Parental & Family Support — Parental leave is consistently described as strong, with supportive maternity and paternity programs. Family support appears alongside core benefits such as health coverage and equity.

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The Company
HQ: Mountain View, CA
650 Employees
Year Founded: 2013

What We Do

The leader in enterprise automation, Workato helps organizations work faster and smarter without compromising security and governance. Built for Business and IT users, Workato is trusted by over 7,000 of the world's top brands like Gitlab, Toast, Broadcom, Intuit, Autodesk, and HubSpot. Leaders use Workato to automate key processes like Order to Cash, Speed to Lead, HR Onboarding and Offboarding and more.

Why Work With Us

Here at Workato, we are a team moved by innovation — a passion to create the best possible way and the drive to continue to make it better. We also believe in the power of our team, knowing that we only succeed if we all succeed together. Our team uses seven operating principles to help us make better decisions, work as a team, and have fun.

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