Data Architect / Product Owner (Platform/Enterprise)

EviSmart; Philippines; On-site; PHP 1,400,000 - 2,000,000; Full time

Job summary

EviSmart is seeking aSenior Data Engineer to own our data platform, ensuring a single source of truth across Sales, Finance, and Product. You will build reliable pipelines, keep data clean, and enable self-serve analytics for teams and AI tools.

You will lead a small team, work with modern data tooling, and ensure near real-time, accessible data for company-wide decisions. This role focuses on a solid foundation for analytics and ML initiatives.

Qualifications

• 4+ years of experience in data engineering with ownership of a production data warehouse or platform end to end.
• Experience building and maintaining a central data warehouse used across teams.
• Strong SQL skills and familiarity with ETL/ELT tooling.

Responsibilities

• Build and run automated data pipelines from multiple systems into one central warehouse.
• Maintain a single, trusted customer and business record across teams.
• Monitor data quality and fix issues proactively before downstream use.
• Collaborate with teams to provide ready, clean, structured data in near real-time.
• Review data structure changes to prevent breaks in warehouse or reports.
• Document data structures to enable direct querying by teams and AI tools.
• Manage and grow a small data engineering team.
• Support a data analyst with access and platform tools for deeper insights.

Skills

Data engineering

SQL

dbt

Airflow

Fivetran

Databricks

Azure Data Factory

Azure Data Lake

Azure SQL

APIs

ML data pipelines

Team leadership

Tools

dbt

Airflow

Fivetran

Databricks

Azure Data Factory

Azure Data Lake

Azure SQL

Job description

About the role

We're looking for a someone to own our company's single source of truth for data. This isn't a back-office infrastructure role - it's the foundation that makes every team's decisions better, from Sales and Finance to the product teams building our newest tools. You'll be responsible for the full data platform: getting data in cleanly from every system we use, structuring it into one trusted warehouse, and making sure that no matter where someone looks across the company, the numbers always match. You'll also help make that data easy enough to use that our teams (and our AI tools) can self-serve most of their own analysis, with you and your team focused on keeping the foundation rock solid.

Key responsibilities

• Build and run reliable, automated pipelines that bring data in from every system - in-house portals, HubSpot, QuickBooks, Jira, and more - into one central warehouse

• Maintain a single, trusted customer and business record so that every team and every system shows the same numbers, every time

• Catch and fix data issues before anyone downstream notices them through monitoring and proactive quality management

• Work directly with teams across the company to understand what data they need, and have it ready - clean, structured, and refreshed in near real-time

• Review any change to how a system structures its data before it ships, so changes never quietly break the warehouse or any report built on it

• Structure and document data well enough that teams and AI tools can query it directly and get the right answer without needing a custom report

• Manage and grow 2 data engineers

• Support a dedicated data analyst with the access and platform tools they need to deliver deeper, custom insights

About you

• 4+ years of experience in data engineering, with a track record of owning a production data warehouse or platform end to end

• Strong SQL skills and hands-on experience with modern data pipeline and ETL/ELT tools (e.g. dbt, Airflow, Fivetran, or similar)

• Experience working with a layered warehouse architecture (medallion architecture - bronze/silver/gold)

• Hands-on experience with Databricks and Azure cloud services (e.g. Azure Data Factory, Azure Data Lake, Azure SQL)

• Comfort integrating data from a mix of in-house systems and third-party platforms (CRM, finance, project management tools)

• Experience exposing data via APIs, or working with teams that consume data through APIs

• Some experience with, or strong interest in, the data needs of ML/AI pipelines

• People management experience, or strong readiness to manage and grow a small team

• Clear communicator who's comfortable partnering directly with non-technical teams to understand what they need