Duties and Responsibilities

Data Infrastructure & Pipeline Engineering

Design, build, and operate scalable data pipelines across Salesforce, Snowflake, and external systems (ticketing, lottery, partners)
Leverage Fivetran and API-based ingestion frameworks to standardize and automate data ingestion from third-party platforms
Own API, webhook and file-based ingestion systems (SFTP, third-party feeds), ensuring reliability and observability
Manage AWS infrastructure supporting data ingestion, processing, and orchestration

Own Snowflake data architecture, including schema design, transformations, and data modeling
Develop and maintain transformation layers using dbt, including modular, testable, and well-documented models
Build canonical datasets and dimensional models supporting analytics, CRM, ticketing, and pricing
Optimize warehouse performance, cost, and scalability through clustering, partitioning, and query optimization
Manage schema evolution and deprecation of legacy data structures

Establish data quality frameworks using dbt tests, monitoring tools, and pipeline validation checks to detect and resolve inconsistencies, duplication, and missing data
Implement automated validation, monitoring, and alerting across pipelines
Own data hygiene standards across customer, order, and transaction datasets

Develop Python-based workflows to automate ingestion, transformation, and operational processes
Reduce manual workflows through system design, tooling, and pipeline reliability improvements
Leverage HighTouch to operationalize data by syncing curated datasets back into Salesforce and other business systems
Partner with third-party developers to maintain ticket lottery systems
Continuously improve pipeline performance, latency, and failure recovery

Build and maintain data pipelines supporting core reporting (sales, marketing performance, partner reporting)
Enable downstream analytics and BI through clean, accessible, and well-modeled datasets

Dynamic Pricing Data Infrastructure & Modeling Support

Own the data infrastructure supporting dynamic pricing models
Design and maintain model-ready datasets across pricing, inventory, and demand signals using Snowflake and dbt
Partner with internal teams and external consultants to operationalize pricing models within Snowflake
Enable rapid iteration, backtesting, and deployment of pricing strategies

Strong proficiency in SQL and advanced data modeling (dimensional + canonical)
Experience building and operating data pipelines using Python and modern data stack tools (Fivetran, dbt, HighTouch or similar)
Deep experience with Snowflake or similar cloud data warehouses
Experience working with CRM systems (Salesforce preferred)
Experience managing data infrastructure in AWS or similar cloud environments
Strong understanding of ETL/ELT design patterns, APIs, and distributed data systems

Reliable, scalable data pipelines with minimal manual intervention
Improved data quality and reduced duplication/errors
Faster reporting and improved data accessibility across teams
Successful deployment and iteration of pricing models supported by robust data systems

Opportunity to lead data architecture strategy, build scalable infrastructure, and directly impact revenue through pricing optimization systems.

Job description provided by Nederlander.
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