Senior Data Engineer

DysrupIT

. Design, build, and maintain data ingestion pipelines for financial and billing data on GCP .

Posted 10/15/2026full-timeRemote • PhilippinesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining data ingestion pipelines on GCP, with a strong focus on financial data accuracy and compliance. Proficient in Python and SQL, with a solid understanding of data quality practices and effective data lineage management.

Highest-signal resume keywords

Data Engineering ExperienceGoogle BigQuery ExpertiseAdvanced SQL SkillsPython ProficiencyInvoicing Domain Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Ingestion PipelinesBigQuery Data ModelsReconciliation ChecksFile Validation ProcessesIdempotent PipelinesAppend-Only Table PatternsPython ProgrammingAdvanced SQLData Quality PracticesData Lineage Management

Soft Skills

CollaborationMentoring

Tools & Technologies

Google Cloud PlatformCloud StorageCloud RunFirestore

Industry Keywords

Financial DataBilling PipelinesEffective-Dated Reference DataCredit NotesRebillsFX ConversionMonth-End Close

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain data ingestion pipelines for financial and billing data on GCP
Design and evolve BigQuery data models, including nested ARRAY/STRUCT tables, partitioning, and clustering strategies
Implement reconciliation checks across source, staging, and output layers
Build file validation and quarantine processes for invalid or incomplete source data
Design idempotent pipelines that can be safely rerun without duplication or corruption
Implement append-only table patterns and use views as data checks to support auditability
Handle monetary values accurately using BigQuery NUMERIC types and appropriate rounding rules
Manage effective-dated reference data such as rates, mappings, and customer attributes
Establish and maintain data lineage from outputs back to sources
Write clean, typed, and well-tested Python code using pydantic and pytest
Write and optimize advanced SQL for transformation, reconciliation, and reporting
Collaborate with engineers, analysts, and finance stakeholders to translate business rules into reliable data logic
Mentor team members and contribute to data engineering standards and best practices

Requirements

What you’ll need

6+ years of data engineering experience
Proven experience building financial or billing pipelines where every amount must reconcile
Strong Python skills, including pydantic, typed code, and pytest
Advanced SQL skills, including complex joins, window functions, and performance tuning
In-depth Google BigQuery experience, including nested ARRAY/STRUCT tables, partitioning, and clustering
Experience handling money accurately using NUMERIC data types
Experience designing append-only tables and using views as data checks
Strong understanding of data quality practices, including reconciliation checks, file validation, and quarantine
Experience building idempotent, rerunnable pipelines
Experience implementing data lineage and managing effective-dated reference data
Invoicing domain experience, including credit notes, rebills, FX conversion, and month-end close
Experience working with finance or billing teams in a regulated or audited environment
Experience with other GCP services such as Cloud Storage, Cloud Run, or Firestore

Benefits

Comp & perks

Competitive compensation package commensurate with experience
Government-mandated benefits
Supplemental HMO coverage
Collaborative and professional work environment
Career growth opportunities within a growing organization
Hybrid/Remote work arrangement (where applicable)
Training to support employee growth and career advancement