Builds and scales data pipelines and infrastructure to ingest, transform, and deliver actionable insights from raw events. Requires 3+ years experience, expert SQL, programming, and ETL/ELT expertise for nationwide marketplace.
Salary not listed
On-site3+ YOEData Engineering
About the role
Primary Responsibilities
Design, implement, and maintain scalable data transformation layers and code-first orchestration frameworks to ensure the delivery of high-fidelity, reusable data models
Design and build robust pipelines to ingest data from diverse sources (APIs, logs, relational DBs)
Ensure the reliable and timely execution of all critical data pipelines (ETLs/ELTs) to maintain data integrity and freshness
Standardize analytics workflows by integrating software engineering best practices, including version control, CI/CD pipelines, and automated data validation protocols
Develop and refine a robust semantic layer to facilitate self-service analytics, enabling stakeholders to derive insights without exposure to underlying architectural complexities
Monitor and optimize cloud compute utilization and data model performance to ensure high availability and low-latency reporting during periods of rapid data scaling
Serve as a strategic technical partner to leadership across Product, Engineering, Marketing, and Finance to align data infrastructure with organizational objectives
Become a subject matter expert on the product ecosystem, user behavior, and marketing life cycles to better translate raw data into business value
Serve as a versatile technical resource capable of stepping into the Data Analyst capacity when necessary—performing deep-dive quantitative analysis and building sophisticated visualizations to support executive decision-making
Mentor the data analytics team on advanced technical methodologies to foster a culture of engineering excellence and data autonomy
Qualifications
3+ years of experience in data engineering or analytics engineering
Bachelor's degree in quantitative and/or technical fields (Math, Physics, Statistics, Economics, Computer Science, Engineering, etc.) OR 5+ years work experience as a Data Engineer
Expert-level mastery of SQL, with the ability to write, tune, and optimize complex queries for high-volume environments
Strong command of at least one major programming language used for data processing
Hands-on experience designing and maintaining data lakes or cloud-based data warehouses
Deep understanding of data integration patterns, including data ingestion, transformation, and automated cleansing (ETL/ELT)
Experience applying scientific, mathematical, or statistical techniques to analyze data and build predictive models
Advanced ability to translate complex datasets into actionable narratives using modern business intelligence and reporting tools
A proven track record of using quantitative analysis to solve ambiguous problems and drive strategic decision-making in a fast-paced environment
Exceptional ability to collaborate with non-technical stakeholders, translating business requirements into technical specs and vice versa
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