Job Description:
Read this part first
This is a role for an engineer who wants to own core components of a modern data platform. We are looking for a Staff Data Engineer to architect, build, and operate production data systems across Prodege. This is a deeply hands-on technical role. You lead by building production-grade systems, setting engineering standards, and delivering scalable data architecture, not by working strictly at an abstract planning level.
If you prefer delegating execution or working solely on isolated pipelines, this is not the role for you. But if you are a technical lead who owns data platforms end to end, from ingestion, streaming, and Medallion modeling to observability, governance, feature store foundations, and deployment, keep reading.
You will build and evolve platform capabilities for a business serving over 120 million registered users. Operating within a high-scale data environment featuring a 400 Terabyte footprint, a 100 Terabyte Iceberg lake, 50 million daily events, and 500 million pipeline records, you will deliver the data foundations that power analytics, experimentation, machine learning, and AI-driven decision making across all Prodege products. If you enjoy building distributed systems at scale, working closely with cross-functional technical teams, and driving an AI-first engineering strategy, this role is for you.
Prodege
A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty and product adoption. Bolstered by a major investment by Blackstone in the first quarter of 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.
What you will own
Architecture, implementation, and operational reliability of major data platform domains, including pipelines, modeling layers, and data services
High-scale batch, ELT, and near-real-time streaming pipelines powering business intelligence, machine learning, experimentation, and product analytics
Platform standards for data governance, schema evolution, data contracts, lineage, and end-to-end observability
Data infrastructure and feature pipelines supporting machine learning, experimentation frameworks, and AI-driven applications
Technical quality and engineering standards across the team through direct code contributions, architecture design reviews, and technical mentorship
What makes this role exciting
You will directly shape core data platform capabilities that drive analytics, machine learning, and business intelligence across the enterprise
You will own major technical domains from initial system design through production deployment and lifecycle management
You will build data foundations across consumer rewards, performance marketing, customer experience, and multiple owned digital properties
You will operate at true engineering scale, managing a 400 Terabyte data footprint, 50 million daily events, 500 million daily pipeline records, 50 plus Kafka topics, and 300 thousand daily queries
You will establish platform patterns that accelerate Prodege transition to an AI-first software engineering model
What you will do
Architect, build, and operate high-capacity batch, ELT, event-driven, and near-real-time streaming data pipelines
Construct production-grade data platform components utilizing Snowflake, dbt, Iceberg, Trino, Kafka, and modern lakehouse technologies
Design scalable data models adhering to Medallion architecture principles to support business intelligence, advanced analytics, and machine learning
Enforce platform discipline around data contracts, schema evolution, lineage tracking, access governance, and system observability
Optimize data infrastructure for performance, query speed, system reliability, availability, and cost efficiency
Partner cross-functionally with Engineering, Product, Analytics, Business Intelligence, and Machine Learning teams to deliver trusted data foundations
Apply AI-assisted engineering tools to accelerate development velocity, automated testing, system debugging, and technical documentation
What you will bring
Five to eight or more years of hands-on data engineering experience building large-scale data systems, ideally in advertising technology, marketing technology, consumer internet, or high-volume marketplace environments
Advanced technical expertise with SQL, Python, Snowflake, and dbt
Demonstrated background designing, deploying, and operating production-grade batch, ELT, and streaming pipeline architectures
In-depth understanding of modern data architecture paradigms, including Medallion architecture, data contracts, schema evolution, event-driven systems, and data modeling
Practical experience building data systems that directly support analytics, experimentation platforms, and machine learning workloads
Proven ability to optimize data pipelines and storage systems for scale, reliability, throughput, and cost performance
Strong communication and technical leadership skills, with a track record of driving technical decisions through design reviews, code reviews, and cross-functional alignment
Bonus points
Experience with Iceberg, Trino, Kafka, Flink, Kinesis, Spark, or related lakehouse and distributed streaming frameworks
Experience building ML feature pipelines, feature stores, or model training data infrastructure
Experience architecting self-service analytics frameworks or experimentation platforms
Experience with modern DataOps methodologies, workflow orchestration, and data observability tools
Experience leveraging modern AI-assisted software development tools to enhance engineering productivity
Pay Transparency:
The anticipated base salary range for this position is $185,000 to $220,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Prodege Benefits:
Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.
Equal Employment Opportunity Statement
At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.
FCIHO
Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.
5+ years data engineering experience building large-scale batch and streaming pipelines; strong SQL, Python, Snowflake, dbt; expertise in data modeling, governance, observability, and ML feature pipelines.
Key Responsibilities
- architecting platforms
- building pipelines
- operating systems
Skills & Tools
SQL, Python, Snowflake, dbt, Iceberg, Trino, Kafka, Flink, Kinesis, Spark
Job Details
- Category: Data and Analytics
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — California, United States
- Salary: USD 185,000 – 220,000 / year
- Languages: English
Benefits
- Generous paid time off
About Prodege
A marketing and consumer insights technology company that builds data-driven platforms to help brands and agencies uncover customer behavior. — Industry: Information Technology