Data Engineer

 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

 

Data Warehouse & Modeling

● 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

Data Quality, Governance & Reliability

● 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

Automation & Systems Optimization

● 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

Reporting & Data Enablement

● 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

 

QUALIFICATIONS

Expertise

● 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

 

What Success Looks Like

● 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

Growth & Development Opportunities

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