Data Engineer
This role involves building and optimizing the data infrastructure that powers analytics, machine learning, and operational decision-making across AI-focused organizations. Data engineers in this position design scalable pipelines to ingest data from infrastructure, product systems, and business operations, then transform that raw data into reliable datasets that serve analysts, data scientists, and product teams. What sets this role apart is its foundation-level focus—rather than analyzing data or building models, these engineers architect the systems, data models, and warehouses that make all downstream work possible. They typically report into data or platform leadership and work cross-functionally with product, engineering, finance, and operations teams to translate business requirements into production-grade data infrastructure that scales with organizational growth.
Measured across 35 of 36 open postings.
This role is advertised at 2 levels, so a single figure for the role would describe none of them. Experience and pay are the midpoints for each level on its own.
| Level | Share | Median years | Median pay |
|---|---|---|---|
| Mid | 51%(18) | 5 | — |
| Senior | 34%(12) | 6.5 | — |
A dash means too few postings stated it to report a midpoint. Most companies do not publish a salary band, so pay is indicative rather than a market rate. 3 levels with fewer than 10 open postings are not shown.
“Use AI-assisted coding tools to build and maintain front ends alongside Python backend serv”
“actively experimenting with AI to transform how we understand and support our workforce”
“Build internal data tools with applied AI, using Serval's own agents to turn recurring data questions into self-serve answers.”
“Leverage AI-assisted engineering tools to improve development and testing productivity”
Requirements are a share of every open posting, so a role missing from this list is one where almost nobody asks. Work mode is different: many postings never say, so that figure counts only the ones that do.
Skills
What companies are looking for in this role.
Data pipeline engineering
Data quality and governance
Analytics data modeling
Database and storage engineering
SQL query development
Cloud and data platform architecture
Dashboarding and self-service analytics
Distributed systems architecture
Monitoring and observability
Backend and API engineering
Cloud infrastructure operations
Infrastructure automation and IaC
Systems performance optimization
CI/CD and release automation
LLM data infrastructure
Agent workflow design
Mentoring and code review
Technology
The tools and technologies that define this role.
Open Jobs
36 open Data Engineer jobs across 25 companies.
Other Data & Analytics roles
Applies statistical modeling, machine learning, and experimentation to extract insights from data.
Bridges data engineering and analytics by building data models, metrics layers, and self-serve analytics tools.
Analyzes data to generate actionable business insights, builds dashboards and reports.
Data professionals specializing in marketing and go-to-market measurement, attribution modeling, and revenue intelligence. Focuses on building analytical frameworks, experimentation, and data-driven insights to optimize GTM strategy. The emphasis is on analytics methodology and data infrastructure for marketing.
Manages data labeling, annotation, and curation operations for machine learning.