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# TELECOMMUTE Data Engineer (Billing & Compensation Data Pipelines)

- **Company:** DKMRBH Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Microsoft Azure, Cloud Database, Directed Acyclic Graph (Directed Graphs), Data Validation, Data Deduplication, Extract Transform Load (ETL), Data Transformation, Data Structures, Software Debugging, Document-Oriented Databases, Job Scheduling, Python (Programming Language), Scrum Methodology, SQL Databases, System Testing, Transact-SQL, Snowflake, Build Management, Data Pipelines
- **Published:** September 3, 2026
- **Apply:** https://www.dice.com/job-detail/fd6ea7c0-d735-4fa0-b051-d7cb2b9ee31c

## About the Role

* Minimum 5 years of relevant professional experience.
 * Strong knowledge of Apache Airflow for job scheduling, orchestration, and DAG development.
 * Strong knowledge of Snowflake SQL and/or T-SQL, including CTEs, window functions, date-based transformations, and multi-source joins.
 * Experience with ETL/ELT development pulling data from on-premise systems into cloud data warehouses.
 * Experience with Python for pipeline scripting, custom operators, and data transformation logic.
 * Strong understanding of revenue and expense data structures.
 * Experience in writing and executing unit/system test cases for data pipelines.
 * Financial industry experience, preferably in investment management or billing/compensation systems.
 * Ability to manage time independently and work independently.
 * Experience with CI/CD pipelines, preferably Azure DevOps.
 * Experience in an Agile/Scrum environment is a plus.
 * Experience debugging SQL views for column mismatches, join errors, and performance issues is a plus.
 * Experience using AI capabilities is a plus.

## Description

* Design and build ETL/ELT pipelines pulling revenue and expense data from on-premise source systems into Snowflake.
 * Develop Airflow DAGs for scheduling, dependency management, retries, and monitoring of data pipeline jobs.
 * Implement calculation logic across multiple data points, such as gross vs. net revenue and expense allocations, in SQL (Snowflake SQL/T-SQL) or Python.
 * Perform data validation, reconciliation, and deduplication to ensure billing/revenue figures are accurate before downstream consumption.
 * Debug and maintain existing SQL views, including identifying column mismatches, join logic errors, and typos.
 * Optimize queries/views to avoid full-table scans and unfiltered CTEs that degrade production performance.
 * Build monitoring/alerting for pipeline failures, data quality issues, and SLA breaches within Airflow.
 * Document data lineage, transformation logic, and calculation rules to support audit and traceability requirements.
 * Collaborate with technical leads and business stakeholders to translate revenue/expense business rules into pipeline logic.


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