Senior Data Quality Engineer [DBT, Snowflake] (AU, Retail, Hybrid)

ConnectOS; Mandaluyong; On-site; PHP 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Hybrid work arrangement (3x onsite)–

Health coverage

Paid time off

Competitive compensation

13th month pay

Job summary

ConnectOS is seeking a senior Data Quality Engineer to lead data quality governance, oversight, and assurance across analytics and data platforms in a hybrid setup in Metro Manila. The role focuses on governance rather than hands-on engineering, requiring leadership to embed quality into data workflows.

Ideal candidates will have 4+ years in data quality or governance, strong standards development ability, and familiarity with dbt and Snowflake.

Qualifications

• Senior-level background (4+ years) in data quality, data governance, or data assurance, with influence over teams.
• Ability to define and enforce data quality standards and best practices at governance level.
• Familiarity with modern data platforms (e.g., dbt, Snowflake) and a proactive mindset.

Responsibilities

• Own and champion data quality standards across the organization.
• Identify recurring data quality issues and guide engineering teams to address root causes.
• Define and promote data quality governance frameworks and guidelines.
• Influence data engineers and analytics teams to embed quality checks in workflows.
• Set expectations with stakeholders around data quality, reliability, and accountability.
• Provide oversight across data pipelines and transformations rather than doing hands-on engineering tasks.
• Develop and refine data quality metrics, monitoring, and reporting.
• Maintain documentation related to data quality standards and responsibilities.

Skills

Data quality principles

Leadership

Governance

Stakeholder influence

Cross-functional collaboration

Tools

dbt

Snowflake

Job description

Schedule: Monday to Friday (7am to 4pm PHT)

Work Setup: Hybrid (3x per week onsite)

Position Summary

• We are seeking a senior-level Data Quality Engineer to lead and mature data quality practices across our analytics and data platform. This role is focused on data quality governance, oversight, and assurance, rather than hands-on data engineering or testing.
• The successful candidate will act as a data quality leader and advisor, responsible for identifying data quality issues, defining and enforcing best practices, and influencing data engineers and stakeholders to embed data quality into everyday data workflows. You will play a critical role in improving trust, reliability, and consistency of data used across the organization.
• This is an ideal role for someone who is passionate about data quality, standards, and governance, enjoys working cross-functionally, and can bring structure and best practices into a growing data environment.

What are we looking for?

• Senior-level background (4+ years) in data quality, data governance, or data assurance, with experience influencing teams rather than executing hands-on engineering work
• Leadership and change-driving capability, guiding data engineers and analytics teams to improve data quality outcomes
• Strong command of data quality principles, including accuracy, completeness, consistency, timeliness, and validity, with the ability to identify and prioritize issues
• Proven experience defining and enforcing data quality standards and best practices, operating at a governance and oversight level
• Familiarity with modern data platforms (e.g., dbt, Snowflake or similar) and a proactive, collaborative, improvement-oriented mindset

Nice to Have

• Prior experience acting as a data quality lead or governance representative
• Previous hands-on experience with daily data engineering or testing
• Exposure to scaling data quality practices in complex or growing data environments
• Experience working in collaborative, agile, or cross-functional teams
• Strong communication skills with the ability to clearly articulate data quality risks and recommendations

What you will do?

• Act as the owner and champion of data quality standards across the organization
• Identify recurring and systemic data quality issues, and work with engineering teams to address root causes
• Define and promote data quality best practices, guidelines, and governance frameworks
• Influence and guide data engineers and analytics teams to embed quality checks and standards into their workflows
• Partner with stakeholders to set expectations around data quality, reliability, and accountability
• Provide oversight and assurance across data pipelines and transformations rather than executing engineering tasks
• Support the development and refinement of data quality metrics, monitoring, and reporting
• Maintain and evolve documentation related to data quality standards, processes, and responsibilities
• Continuously assess opportunities to improve data quality maturity across the platform

Join the awesome team and enjoy these benefits & perks:

• Hybrid Work Arrangement (3x onsite)
• Medical, Dental Coverage and Life insurance from day 1 of employment
• Paid Vacation and Sick Leave (with Quarterly Sick Leave Conversion)
• Competitive salary package and annual appraisal
• Financial Assistance Program
• Mandatory Government Benefits and 13th Month Pay
• Complimentary Sleeping Quarters, Coffee at no cost
• Complimentary Office Fitness and Wellness Facilities at no cost
• Regular Company Events, Work Life Balance, and Career growth opportunities
• Accessible location at the heart of Metro Manila --- the Mega Tower, EDSA

Employment decisions at ConnectOS will be conducted without consideration of factors such as age', race, color, religion, gender, disability status, sexual orientation, gender identity or expression, genetic information, and marital status. ConnectOS ensures the full confidentiality of the data it processes.