Staff Data Engineer

Kueski; Philippines; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Kueski is seeking a Staff-level Data Engineer to lead the technical strategy and architecture of their data platform in the Philippines. The ideal candidate will have experience in driving complex data initiatives, mentoring engineers, and designing scalable data solutions.

This role requires deep expertise in Python, SQL, Apache Spark, and cloud services like AWS. You will be tasked with ensuring data quality, leading engineering standards, and collaborating with cross-functional teams to deliver impactful data-driven solutions.

Qualifications

• Deep expertise in data engineering at scale, including architecture design.
• Proven leadership in delivering large-scale, complex data platform initiatives.
• Familiarity with AI-enabled tools for coding and system design.

Responsibilities

• Define and implement the data engineering technical strategy and architecture.
• Lead large-scale data initiatives from problem definition to production.
• Mentor and elevate data engineering teams through guidance and best practices.

Skills

Expert-level programming in Python

Strong SQL fundamentals

Expert-level Apache Spark experience

Experience with AWS and Google Cloud services

Experience with CI/CD pipelines

Tools

Databricks

Scala

Java

Job description

Position

Kueski is seeking a Staff-level Data Engineer to drive the technical strategy, architecture, and long-term evolution of our data platform.

This role is ideal for a deeply technical leader who thrives in complex, ambiguous environments and can deliver scalable data solutions from problem definition through production.

As a key leader in Data Engineering, you will own platform direction, establish engineering standards, and lead large-scale initiatives across batch, streaming, AI-centric, and governance capabilities.

Reporting to the Sr Manager of Data Engineering, you will partner across Data Science, ML, Analytics, Platform, and Product to build reliable, high-impact data systems.

You will mentor engineers at all levels, elevate technical quality, and make architecture decisions that directly support Kueski’s business objectives and long-term platform health.

Key Responsibilities

Technical Strategy, Architecture & Platform Roadmap

• Define and drive the data engineering technical strategy, architecture decisions, and platform roadmap aligned to company objectives
• Lead and deliver large-scale, complex data initiatives—spanning multiple teams and iterations—from ambiguous problem definition through production deployment
• Design robust, scalable data architectures (batch and streaming) that support Kueski's long-term business needs at scale
• Demonstrated success shaping and executing an AI-centric data strategy that leverages the latest AI technologies to accelerate value delivery, enable trusted self-service data consumption, and strengthen data quality, governance, and organizational decision-making.
• Identify the limits of existing tools or processes; lead the design and build of new capabilities when current solutions fall short

Engineering Excellence, Standards & Platform Reliability

• Shape, standardize, and champion data engineering methodologies, best practices, and technical standards for the team and department
• Develop and own CI/CD pipelines and infrastructure-as-code for reliable, automated data platform operations
• Drive data quality, observability, and governance programs across the data platform
• Apply data cleansing techniques to facilitate data consumption and quality across the platform

Cross-functional Leadership & Organizational Impact

• Partner cross-functionally with Data Science, ML, Analytics, Platform, and Product teams to deliver data-driven solutions end-to-end
• Represent data engineering in cross-organizational initiatives; support and lead efforts outside the core area of responsibility

Mentorship, Technical Enablement & Team Elevation

• Mentor and guide Data Engineers at all levels; constructively challenge assumptions and elevate team quality through code review, pairing, and coaching

Experience

• Deep expertise in data engineering at scale: architecture design, performance optimization, and production operations
• Proven leadership delivering large-scale, complex data platform initiatives—from ambiguous problem scoping through stable production
• Experience using AI-enabled tools for coding, productivity, and system design. Including implementation of AI adjacent infra such as MCP Server, RAG, etc.
• Expert-level programming in Python; strong SQL fundamentals; Scala/Java is a plus. Typescript is optional.
• Expert-level Apache Spark experience; deep knowledge of distributed data processing patterns and optimization techniques
• Extensive experience designing and building robust, production-grade data pipelines (batch and near-real-time)
• Deep understanding of data modeling practices such as star schemas and dimensional modeling.
• Strong command of big data cloud services (i.e., AWS, Google Cloud) and data platforms such as Databricks.
• Proven experience defining and implementing CI/CD pipelines and infrastructure-as-code (IaC) for data workloads
• Proven experience working with modern data architectures such as medallion layer, data lakehouses, data products, and adjacent patterns.
• Strong grasp of software design patterns, SDLC best practices, and non-functional requirements at scale
• Track record of mentoring and elevating data engineering teams; recognized as a technical leader and subject matter expert
• Broad collaboration experience with ML, Analytics, Platform, and Product teams on cross-functional data initiatives
• Experience driving data quality, observability, and governance programs at scale.

Diversity & Inclusion

At Kueski we embrace diversity in all forms, systematically promote equity, and ensure everyone feels included with a sense of belonging. We are committed to the full inclusion of all qualified candidates. As part of this commitment, we will make efforts to ensure reasonable accommodations are made during the hiring process. If reasonable accommodation is needed, please let the Talent Acquisition team know.