Customer engineer (data engineer)

In this role, you will be the technical point of contact for the customer – a trusted partner for their IT leadership – as the primary engineer on the project, working with multifunctional teams both internally and externally. You are a customer-facing data engineer who genuinely loves solving problems and can handle client expectations while working on complex technical issues under pressure.

You’re comfortable working across diverse teams and are not afraid to dig into data and code to deliver results. You thrive in high-stakes environments and understand what it means to be a trusted technical partner to some of the world’s largest enterprises.

Key Responsibilities : Customer Engineers are the technical owners of post-sale customer success, responsible for implementing and supporting Marketing AI solutions.

You will :

Work hands-on with Uniphore’s CDP platform and supporting components to implement data pipelines and integrations

Collaborate with Solution Architect, Solution Consultants, Engagement Managers and Product Engineering, to deliver on complex customer use cases

Act as the primary technical contact and trusted advisor for customers along with the Solution Architect

Coach and mentor junior Engineers on the team

Design and configure workflows based on client business needs using SQL, Python, and cloud infrastructure

Build data models that support personalization, lookalike modeling, and omnichannel activation

Set up ETL pipelines across disparate sources and create unified customer views

Configure Uniphore product features and external data connections (APIs, S3, etc.)

Produce detailed technical documentation

Proactively identify and resolve blockers to ensure project timelines are met

Serve as a source of feedback for our product team, full stack and backend engineering teams

Qualifications :

BS degree in Computer Science, Engineering, Mathematics, Economics, Statistics, Information Management or similar

6+ years of experience in a customer-facing Saa S solution implementation that involves managing and manipulating large data sets, such as ETL, Data Warehousing, Analytics

Proficiency in SQL, troubleshooting large-scale relational datasets, scripting (e.g., Python, Ruby, Shell), and working with cloud-based systems (AWS preferred)

Strong understanding of RESTful APIs, including usage through Postman or c URL

Experience setting up ETL processes and integrating disparate data sources

Working knowledge of data modeling and customer data infrastructure (CDP, CRM, DMP, etc.) and experience in data exploration

Experience with APIs and basic familiarity with cloud data warehouses (e.g., Snowflake, Redshift), and deployment best practices

Strong mindset of independent ownership of a deliverable end to end. Ability raise risks, prioritize, estimate time and effort, advise non-technical stakeholders on dependencies is critical

Strong customer-facing verbal and written communication skills in English

Ability to explain complex technical problems to both technical experts and non-technical stakeholders

Proficiency in typical SDLC methodologies; hands-on experience in Agile development and proficiency in tools like Asana, Jira, Smartsheet, etc.

Customer-first and data-obsessed mindset

Passion for learning and preferably hands-on experience with agentic AI solutions, including prompt engineering and context design