Senior Disputes Data Engineer

Velera

1d•$95,800 - $124,500•Remote

About The Position

The Senior Data Engineer is responsible for architecting, designing, developing, and optimizing enterprise-scale data platforms, analytical data models, and data integration solutions. This role involves designing and building data structures, schemas, and pipelines from the ground up, rather than solely maintaining existing assets. The position also provides technical leadership across SQL engineering, ETL/ELT development, cloud platforms, API integrations, data modeling, performance optimization, and enterprise data governance.

Requirements

Minimum 5+ years of progressively responsible experience in Data Engineering, Data Warehousing, Analytics Engineering, Data Integration, Business Intelligence, or related disciplines.
Demonstrated experience building enterprise-scale data architectures, ETL/ELT pipelines, and cloud-based data platforms.
Experience integrating data from APIs, databases, flat files, cloud platforms, and third-party applications.
5 years of experience in SQL development (including query creation and modification, dataset creation, table maintenance, and large-scale data analysis) or MIS reporting and analysis required.
2 years of experience creating and modifying macros, queries and tables.
Power BI expertise including DAX, Power Query, data manipulation, complex visualizations, dashboards, and calculations.
Data modeling, ETL/data pipeline, and metadata governance experience.

Nice To Haves

Knowledge of disputes, chargebacks, fraud operations, and case-management systems preferred.
Experience working with other BI tools such as Qlik Sense, and Tableau

Responsibilities

Design, develop, deploy, and optimize enterprise-scale data solutions supporting analytics, reporting, business intelligence, and operational workloads.
Architect and build scalable data structures, schemas, dimensional models, and enterprise data pipelines from the ground up.
Design, develop, optimize, and support ETL/ELT frameworks and automated data integration processes.
Develop and maintain API integrations and automated data-ingestion frameworks supporting multiple internal and external source systems.
Design and implement cloud-native data solutions utilizing Azure, AWS, Snowflake, Databricks, Synapse Analytics, or equivalent technologies.
Lead database performance tuning initiatives including indexing strategies, workload optimization, execution-plan analysis, and query optimization.
Develop expert-level SQL solutions utilizing CTEs, window functions, advanced joins, stored procedures, analytical functions, and relational modeling principles.