As the first dedicated data engineer on an AWS Marketplace B2B Marketing data science team, you will help build the foundation for marketing intelligence that runs across the full machine learning lifecycle. This onsite role in Herndon, VA combines data infrastructure, production pipelines, and model-ready datasets to support systems that power attribution, targeting, experimentation, and partner intelligence.
You will own the data capabilities that enable customers to discover, evaluate, and purchase third-party software, while helping the team move toward an end-to-end intelligent B2B marketing platform where data science and AI drive key decisions.
What youβll do
- Design, build, and operate production data pipelines that serve ML models and analytics, including feature engineering, model scoring infrastructure, output delivery, and data quality enforcement.
- Define and own the teamβs data architecture, balancing trade-offs across speed versus durability, cost versus scalability, and short-term delivery versus long-term maintainability.
- Build analytical datasets that connect product activity, marketing engagement, customer transactions, and revenue into query-ready models for analysis that wasnβt previously possible.
- Deliver well-documented, maintainable code designed for other engineers to extend, using patterns and templates that raise data quality across the team.
- Partner across disciplines with data scientists, marketers, and cross-functional engineering teams to gather requirements, define data contracts, influence upstream producers, and support downstream self-serve consumption.
Core qualifications
- 5+ years of data engineering experience
- Experience with data modeling, warehousing, and building ETL pipelines
- SQL experience
- Experience with at least one modern scripting or programming language: Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
Preferred
- Experience with Hadoop, Hive, Spark, and EMR
- Experience operating large data warehouses
Day-to-day scope
Your responsibilities span ingestion from multiple data platforms, feature engineering for model training, deployment of production pipelines, model output delivery, and the reporting layer that makes results usable for the business. Some initiatives will be clearly defined, while others will require you to define the execution path as ambiguity arises. You will work across data modeling, pipeline engineering, infrastructure automation, and direct collaboration with data scientists on systems that are new to production.
Tools and technologies
SQL, Python, Java, Scala, NodeJS, Hadoop, Hive, Spark, EMR
Compensation and benefits
Salary: USD 154,600 - 209,100 per year.
- Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- Paid time off
- Parental leave
- Sign-on payments
- Restricted stock units (RSUs)
