Sr. Data Engineer - PH
At a glance
Senior Data Engineering role at Pandoblox. Remote · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Set up client data feeds from ODBC, APIs and files, then compare warehouse row counts and values with source systems
- Run pipelines across client work, resolving stale data, failures, incidents and infrastructure cost issues
- Build isolated dbt projects and models that match clients’ source figures, with reconciliation records for sign-off
- Turn client discovery into metric definitions, business marts and tested data for dashboards and AI queries
- Maintain automated data checks, freshness alerts, PII awareness and structured operational traces
What you bring
- At least seven years delivering end-to-end work in data or analytics engineering
- Experience in at least two listed industries, such as sales, marketing or finance
- Production expertise with cloud warehouses and dbt Core, including query and cost optimization, modeling and automated tests
- A track record integrating complex business systems and reconciling their data with source reports
- Strong English communication and the ability to lead discovery with non-technical stakeholders
Who this fits
This suits a senior individual contributor who wants to stay hands-on with dbt and warehouse work while also handling client discovery and analysis. You must reside in the Philippines and work Pacific hours or client hours as needed. The role is remote, with a ninety-day probation period and a requirement to install endpoint protection.
From the employer
ABOUT THE ROLE:
Pandoblox is building the future of data consulting by leveraging an elite team of practitioners amplified by AI to deliver enterprise-quality data platforms (Signal OS) to mid-market companies. We are looking for a Senior Data Engineer who balances a mastery of data-engineering craft with a strong data analyst edge. This is a hands-on, individual contributor delivery role where you will transform raw source systems into trusted, governed data marts that drive executive decisions and feed AI agents.
The position is structured around roughly 70% hands-on building, 25% client domain discovery/analysis, and 5% collaborator engineering practices.
RESPONSIBILITIES:
In this role, you'll get to...
- Stand up and operate per-client data ingestion (ODBC, API, and file sources) into the warehouse via our ELT layer.
- Run rigorous row-count and parity checks to verify raw landings directly against the client’s source systems.
- Own end-to-end pipeline operations across concurrent clients, directly diagnosing freshness issues, failure alerts, infrastructure costs, and incidents.
- Build and maintain isolated, three-layer dbt projects (staging → intermediate → marts) for each client assignment.
- Construct robust fact and baseline models that reproduce a client’s exact source-of-truth numbers, producing reconciliation documentation for client sign-off.
- Perform engineering standards rigor by applying version-controlled, tested, peer-reviewed, and reproducible data practices utilizing a disciplined local-to-CI workflow.
- Apply right-size engineering rigor appropriately for a startup environment, partnering cleanly with platform engineering without gold-plating solutions.
- Sit directly with client operators, controllers, and analysts to pull essential domain logic and uncover system patterns.
- Translate discovery conversations directly into clear metric definitions within the semantic layer and queryable business marts.
- Own core business-rule tests and metric definitions (Cube.dev) powering executive dashboards and natural-language AI querying.
- Construct the quality framework using automated dbt tests, anomaly checks, freshness monitoring, and PII awareness.
- Optimize and structure context-rich datasets with clean joins and clear descriptions so AI agents can reason correctly via the signal-mcp tool server.
- Ensure all ongoing data operations capture structured traces that continuously feed our cross-client intelligence layers.
- Collaborate and train other team members
- Perform other duties as required by the role
REQUIREMENTS:
On day one, we'll expect you to…
Have 7+ years of experience in data engineering or analytics engineering, with a proven history of delivering trusted data end-to-end.
Have experience in at least 2 of these industries: Sales, Marketing, Finance & Finance related, Media
Possess deep, hands-on production ownership of cloud data warehouses, focusing heavily on query optimization, cost strategy, partitioning, clustering, and dataset architecture.
Have deep knowledge for cloud data warehouse production experience, with Google BigQuery strongly preferred (Snowflake, Redshift, or equivalent is acceptable).
To be expert-level capabilities with dbt Core, building production projects from scratch, managing layers, and setting up automated testing frameworks.
Have strong dimensional modeling foundations, including Kimball methodologies, conformed dimensions, and canonical entity design.
Have proven capabilities integrating and unifying data from complex systems such as ERP (NetSuite, SAP), CRM (Salesforce, HubSpot), and HRIS (ADP).
Possesses the ability to confidently lead discovery workshops with non-technical executive stakeholders, controllers, and operational leads.
Have a track record of shipping right-sized, trustworthy data outcomes under fast-paced startup or multi-client consulting settings.
Have an experience operating within capable teams utilizing modern Git practices, branching, code reviews, and keyless production deployments via CI.
Possesses motivation to remain a hands-on builder in dbt and BigQuery daily, supported by AI agent tooling rather than transitioning into people management.
Possess capability to easily wear the analyst hat, extracting business needs, reverse-engineering domain models, and reconciling numbers against source-of-truth reports.
Have strong written and verbal English communication skills
Have a fully functional and up-to-date computer with which to perform duties
Be willing to install next generation end point protection on the computer
Be a current resident of the Philippines and can perform work from there
Be willing to work within US Pacific timezone (8am - 5pm PST, 12AM - 9AM Manila time) or during client hours as required
Be willing to undergo a 90-days probationary period upon initial hire
NOTE:
- This is a remote (work from home) job
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