Staff Data Engineer

- ThoughtSpot / Power BI – data modeling, embedding, semantic layer design. - Python / PySpark – data transformations and automation. - Airflow, Informatica IICS, or equivalent for orchestration.

- Snowflake – modeling, performance optimization, RBAC, and data sharing. - SQL – advanced queries, window functions, analytical optimizations. - ThoughtSpot / Power BI – data modeling, embedding, semantic layer design.

- Airflow, Informatica IICS, or equivalent for orchestration. - Azure ecosystem – ADLS, ADF, and related services. - Strong understanding of data modeling patterns (star schema, Iceberg, medallion architecture).

Quality & Observability - Implement data validation and quality frameworks (e.g., dbt tests, Great Expectations). - Monitor data freshness and pipeline health through observability tools and Snowflake monitoring.

Preferred - Hands-on with dbt, Great Expectations, or similar data quality frameworks. - Experience embedding analytics through ThoughtSpot Everywhere or APIs.

- Experience embedding analytics through ThoughtSpot Everywhere or APIs. - Knowledge of Iceberg table management, webhooks, and event-driven pipelines. - Background in healthcare, benefits, or financial data domains.

Why Join Us You’ll be part of a mission-driven team building the next generation of data and analytics platforms for Health & Benefits at Wex. Work hands-on with modern technologies (Snowflake, ThoughtSpot, Airflow, Iceberg, Kafka, IICS, APIs) to deliver real-world impact through high-quality data and reporting solutions.

- Strong understanding of data modeling patterns (star schema, Iceberg, medallion architecture). - Familiarity with Kafka / Debezium for CDC-based ingestion. - Experience building or consuming REST / GraphQL APIs for data products.

About the Team The Health & Benefits (H&B) Data Products & Reporting team delivers scalable, high-quality data products and reporting solutions for WEX’s H&B business. We operate downstream of the Enterprise Data Platform, consuming curated and conformed data to power Snowflake, ThoughtSpot, Power BI, and API-driven reporting experiences. Our goal is to transform complex data into accurate, accessible, and actionable insights — empowering clients, operations, and product teams through data-driven decision making.

Architecture & Design - Architect and implement scalable reporting data models in Snowflake to support ThoughtSpot and Power BI consumption. - Design and maintain robust semantic models, data sharing mechanisms, and APIs for downstream consumers.

- SQL – advanced queries, window functions, analytical optimizations. - ThoughtSpot / Power BI – data modeling, embedding, semantic layer design. - Python / PySpark – data transformations and automation.

Role Overview As a Staff Data Engineer, you will serve as a key technical leader in designing and implementing data and reporting solutions across the Snowflake consumption layer and our reporting ecosystem. You’ll work closely with the Data Platform, Product, and Analytics teams to build reliable data pipelines, reporting models, APIs, and self-service tools that ensure trust, transparency, and performance in our data products. This role combines data platform expertise with reporting system design — ideal for someone who can bridge upstream data architecture with downstream business intelligence needs.

- Build performant, reusable data transformations and APIs for reporting and dashboards. - Integrate with Snowflake Data Sharing, webhooks, and REST/GraphQL endpoints to deliver customer-facing insights. - Lead proof-of-concepts for new reporting frameworks and data sharing capabilities.

- Implement data validation and quality frameworks (e.g., dbt tests, Great Expectations). - Monitor data freshness and pipeline health through observability tools and Snowflake monitoring. - Collaborate with DAAS and Platform teams to triage and resolve data quality issues.

- Partner with product managers, analysts, and business stakeholders to translate requirements into scalable data solutions. - Mentor engineers in data modeling, performance tuning, and best practices for Snowflake and BI systems. - Contribute to documentation, standards, and architecture reviews.

- Deep expertise in: - Snowflake – modeling, performance optimization, RBAC, and data sharing. - SQL – advanced queries, window functions, analytical optimizations.

- Python / PySpark – data transformations and automation. - Airflow, Informatica IICS, or equivalent for orchestration. - Azure ecosystem – ADLS, ADF, and related services.