Senior Data Engineer

ABOUT DYSRUPIT
DysrupIT is a leading global-based cloud services company. We support clients across the globe in their adoption of the cloud and their transformation to as-a-Service business models. DysrupIT is dedicated to making a positive impact in the communities it serves.
COMPANY CULTURE
We are constantly looking for talented people to join our team. We offer a unique and extraordinary career experience to motivate and inspire talents like you to make a difference in our customers, clients, and the entire organization. At DysrupIT, you’ll join a team of dedicated and brilliant professionals who share the same goal of pursuing integrity and excellence. We are committed to promoting a culture where employees are valued and respected. We invest in our employees and make sure that they will have the right training to secure their growth and advancement towards their career aspirations.
JOB SUMMARY
We are seeking a Senior Data Engineer to own the ingestion, data model, and reconciliation layers of a financial billing and invoicing data platform built on Google Cloud Platform (GCP). This role is responsible for ensuring that every amount flowing through the platform is accurate, traceable, and fully reconciled.
The ideal candidate has 6+ years of data engineering experience, including financial or billing pipelines, with deep BigQuery expertise and strong Python and SQL skills. You will design robust, auditable data pipelines with built-in data quality controls, and work closely with engineers and business stakeholders to deliver trusted financial data.
JOB RESPONSIBILITIES
Design, build, and maintain data ingestion pipelines for financial and billing data on GCP.
Design and evolve the BigQuery data model, including nested ARRAY/STRUCT tables, partitioning, and clustering strategies.
Implement reconciliation checks to ensure every amount balance end to end across source, staging, and output layers.
Build file validation and quarantine processes to detect, isolate, and report invalid or incomplete source data.
Design idempotent pipelines that can be safely rerun without duplicating or corrupting data.
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 so that every output can be traced back to its source.
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.
REQUIRED TECHNICAL SKILLSET
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.
PREFERRED EXPERIENCE
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.
WHAT WE OFFER
Competitive compensation package commensurate with experience.
Government-mandated benefits plus supplemental HMO coverage.
Collaborative and professional work environment.
Career growth opportunities within a growing organization.
Hybrid/Remote work arrangement (where applicable).

Employment type
Full-Time

Work arrangement
Yes