Data Engineer

Qualifications:

Education: Bachelor’s degree in computer science, data engineering, data science, statistics, or a related field, or equivalent experience.

Certifications: Certifications are not required. Hands on experience with Snowflake and Databricks is valued over certification. Active certifications in either, or in Microsoft Fabric, are a plus.

Work Experience: A minimum of 3 years of relevant technical experience across data engineering and data science, including hands on experience preparing and managing data for data science use cases. Customer facing sales experience is required, gained in a presales, consulting, solutions engineering, reseller, or systems integrator setting. The ideal candidate is a data scientist who has had to prepare and manage their own data, or a data engineer who has worked closely with data scientists and understands their needs.

Specialized Knowledge, Skills, and Abilities:

• Hands on experience with Snowflake and/or Databricks is highly desirable, as most customers we meet use one or both. Exposure to Microsoft Fabric and similar modern data platforms is also relevant.

• Data engineering fundamentals, including data ingestion and integration, ETL and ELT pipeline design, orchestration, batch and streaming processing, SQL, Python, and Apache Spark, data modeling, data quality and observability, and metadata and lineage.

• Working data science experience, including feature engineering, model development and evaluation, and experimentation. A PhD is not required. The requirement is enough depth to hold credible peer conversations with customer data scientists and to understand what they need from data platforms.

• Practical understanding of how AI workloads, including large language models (LLMs), retrieval augmented generation (RAG), and agentic AI, consume enterprise data. The emphasis is on explaining why data readiness determines whether these solutions work, not on building agents for customers.

• Cloud familiarity from a data and AI perspective, including the ability to move and use data from AWS, Azure, Google Cloud, or Alibaba Cloud environments in AI initiatives. Deep cloud infrastructure expertise is not required.

• Working knowledge of enterprise data governance, security, and data strategy, and how trusted data enables successful AI initiatives.

• Strong communication skills, with the ability to speak with data engineers, data scientists, architects, developers, IT leadership, and executive stakeholders, tailoring technical depth appropriately while maintaining credibility with every audience.

• Advisory mindset and the ability to lead customers through ambiguous technical challenges, structure discovery conversations, identify gaps, evaluate platform tradeoffs objectively, and deliver actionable recommendations.

• Sales experience and commercial awareness to support account teams effectively in fast moving sales cycles, including working as a guest in accounts owned by others.

• Genuine curiosity and a habit of staying current. The technologies at the center of this role are new, and the right candidate has learned them by using them and is actively exploring how AI is changing the way data work gets done.

• Familiarity with complementary technologies such as dbt, Apache Airflow, Azure Data Factory, Kafka, or comparable orchestration and integration platforms.

• Familiarity with enterprise AI platforms such as Azure AI, AWS SageMaker, Google Vertex AI, Databricks Mosaic AI, Snowflake Cortex, NVIDIA NIM, or similar technologies.

• Experience using AI tools and coding assistants, such as Claude, Glean, Copilot, and CoCo, with cloud and on premises data platforms.

• Experience presenting technical recommendations to customers and executive leadership.

• Fluent English required. Additional Asia Pacific languages are valued.

• A passion for helping customers solve complex business problems through trusted data foundations and practical AI.

Working conditions (if needed)

This is a hybrid position based in the Singapore office, with two to three days per week in the office. Hours are primarily Asia Pacific business hours, with occasional flexibility for meetings with the US based team. Travel is expected, primarily to Australia and other markets in the region, and will be kept below 50 percent of working time. Due to the pace of AI and Data technology adoption, this will be a fast paced position, juggling multiple active engagements.

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The role demands a high degree of autonomy. As the first team member in the region, the candidate will independently manage tasks and responsibilities while maintaining close virtual collaboration with a team based primarily in the US. The ability to self motivate and drive initiatives forward is critical.

The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has
one of the best. We offer the following benefits to all full-time employees:
• Health and Wellbeing: Heath, Dental, and Vision Care, Onsite Health Centers, Employee
Assistance Program, Wellness program
• Financial Benefits: Competitive pay, Profit Sharing, PF Plan with Company Matching, NPS
(National Pension Scheme), Life and Disability Insurance, Tuition Reimbursement
• Paid Time Off: PTO & Holidays, Parental Leave, Sick Leave, Day of Caring for social
responsibility, Bereavement
Note: This is not an all-encompassing list and should not be used as a complete description of the
plan’s benefits.
We strive to create an environment where all employees are empowered to succeed based on their
skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages
innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All!

If you require accessibility accommodation(s) or adjustment during any stage of the hiring
process, please let your WWT Recruiter know. The recruiter will work with you to understand your
needs and help ensure an accessible experience throughout the interview process.

World Wide Technology (WWT) strives to make a new world happen. WWT's work benefits clients and partners as much as it does its people and community across the globe. Founded in 1990, WWT brings together strategy, deep technical expertise and world-class partnerships to help public and private sector organizations design, build and scale intelligent AI, digital, cybersecurity, cloud and infrastructure solutions. Through its Advanced Technology Center (ATC)—a collaborative ecosystem featuring state-of-the-art hardware and software—WWT enables clients and partners to conceptualize, test and validate innovative technology and then deploy solutions at scale using its global integration and distribution capabilities. With more than 14,000 team members and over 60 locations globally, WWT's culture—grounded in core values and leadership philosophies—has been recognized by Fortune® and Great Place to Work for its commitment to innovation, trust and creating a great place to work for all. WWT provides products and services to large enterprise, global service provider and public sector clients in up to 130 countries across six continents. Softchoice, a World Wide Technology company, supports commercial and SMB markets in the U.S. and Canada. Want to work with highly motivated individuals on high-performance teams?

Join WWT today!

What will you be doing?

The AI & Data Solutions team operates as a presales advisory practice within WWT’s GS&A organization. We help organizations move from AI interest to AI impact, translating complexity into strategy, guiding customers through data and AI readiness, and converting opportunity into services engagements. This is the first team role based in the Asia Pacific region, covering Singapore, Sydney, and the broader market. The primary focus is the region, but the role supports global AI and data solutions work from a Singapore base. The employee will help the team scale globally and may be called on from time to time to support opportunities outside the region. It brings together data engineering depth, working data science experience, and modern AI fluency to help customers get their data ready for AI. This is a presales advisory role, not a delivery role: you will partner with account teams across the full sales cycle, bringing technical credibility and business clarity to every customer conversation. Because you will be the only team member in the region for some time, you will be expected to speak credibly to both customer data engineers and customer data scientists.

Responsibilities:

• Presales Engagement: Join account teams in customer meetings across the Asia Pacific region, delivering briefings, workshops, discovery sessions, and architecture reviews. Support account teams as a trusted guest in their accounts, bringing technical credibility and business clarity to each conversation.

• AI Data Readiness Advisory: Guide customers through getting their data ready for AI, including data pipelines for AI workloads, analytics readiness, data quality, and the practical path from data foundation to AI value.

• Data Engineering and Data Science Bridge: Serve as the regional subject matter expert across both disciplines. Hold peer level conversations with customer data engineers and data scientists, and help each side understand what the other needs from the data.

• Opportunity Support: Support opportunities across the AI Studio, AI Foundry, and AI Factory offerings, qualifying services opportunities and handing them off to the appropriate services teams.

• Regional Messaging and Content: Build customer briefings and develop messaging aligned to what customers across the region care about most, and contribute to team thought leadership and internal enablement content.

• Business Translation: Translate complex technical concepts into language that resonates with business and executive stakeholders by connecting technology directly to outcomes.
• • Partner Ecosystem Engagement: Engage with WWT’s AI Proving Ground and partner ecosystems, particularly Databricks and Snowflake, along with Microsoft Fabric, to develop insights, validate approaches, and support field enablement.
  • Global Team Collaboration: Help the team scale globally by sharing regional insight with the US based team and bringing global assets, demos, and best practices into the Asia Pacific market. Support opportunities outside the region from time to time as needed.