Senior Data Engineer

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Pandoblox

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

☁️ SaaS

🔒 Cybersecurity

🤝 B2B

SaaS • Cybersecurity • B2B

Pandoblox is a B2B software company offering Pandoblox Signal, a fully-managed data platform that connects, normalizes, and visualizes data from ERP, CRM, inventory, and other critical systems to provide a single source of truth and AI-generated insights. The company also provides PandobloxONE, an integrated service desk that unifies IT operations, security monitoring, and data ops into one workflow, along with cybersecurity and identity protection services (Zero Trust, IEM) and compliance support (SOC 2, PCI-DSS, HIPAA). Targeting mid-market enterprises, Pandoblox delivers real-time data processing, 24/7 support, automation, and fractional enterprise expertise to accelerate implementations and reduce operational costs.

📋 Description

• 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

• 7+ years of experience in data engineering or analytics engineering • Experience in at least 2 of these industries: Sales, Marketing, Finance & Finance related, Media • Deep, hands-on production ownership of cloud data warehouses, focusing heavily on query optimization, cost strategy, partitioning, clustering, and dataset architecture • Deep knowledge for cloud data warehouse production experience, with Google BigQuery strongly preferred (Snowflake, Redshift, or equivalent is acceptable) • Expert-level capabilities with dbt Core, building production projects from scratch, managing layers, and setting up automated testing frameworks • Strong dimensional modeling foundations, including Kimball methodologies, conformed dimensions, and canonical entity design • Proven capabilities integrating and unifying data from complex systems such as ERP (NetSuite, SAP), CRM (Salesforce, HubSpot), and HRIS (ADP) • Ability to confidently lead discovery workshops with non-technical executive stakeholders, controllers, and operational leads • Track record of shipping right-sized, trustworthy data outcomes under fast-paced startup or multi-client consulting settings • Experience operating within capable teams utilizing modern Git practices, branching, code reviews, and keyless production deployments via CI • Motivation to remain a hands-on builder in dbt and BigQuery daily, supported by AI agent tooling rather than transitioning into people management • Ability to easily wear the analyst hat, extracting business needs, reverse-engineering domain models, and reconciling numbers against source-of-truth reports • Strong written and verbal English communication skills • Fully functional and up-to-date computer with which to perform duties • Willing to install next generation end point protection on the computer • Current resident of the Philippines and can perform work from there • Willing to work within US Pacific timezone (8am - 5pm PST, 12AM - 9AM Manila time) or during client hours as required • Willing to undergo a 90-days probationary period upon initial hire

🏖️ Benefits

• Flexible schedules • Ability to balance home life with work-life