Skill demonstrated
Every active member writes graded SQL, Python, or Spark on the platform. The audience is who they say they are because we watched them prove it.
For partners
DataDriven.io is where data engineers practice for interviews
Reach out while users are making the decisions you care about: which tools to use, where to work next.
For hiring teams
Data practitioners
These are the users who practice hard to perform optimally in their next interview. They're solving problems in SQL, Python, Spark, architecture, and data modeling long before they take a meeting with your recruiter.
For developer relationships
Deliberate attention
Practice sessions are a focused context. Data engineers are in learning mode, encoding what they see alongside the skills they're building. Your brand becomes part of how they think about the work.
68%
Influence the data tooling stack at their employer
94%
Actively interviewing or open to a new role
73%
Plan to evaluate a new data tool in the next year
3.4
Active sessions per member, per week
Audience composition
Who you reach
Every active member has executed graded SQL, Python, or Spark on the platform. The numbers below are derived from timestamps and graded submissions. Pick an attribute to see the breakdown.
Senior IC (5 to 10 yrs)41%
Mid IC (3 to 5 yrs)27%
Staff & Principal (10+ yrs)12%
Lateral from SWE or analytics14%
Early career6%
SQL (windowing, CTEs)94%
Python (transforms, pipelines)81%
PySpark or Spark SQL58%
Data modeling, dimensional49%
Pipeline or system design37%
Streaming (Kafka, Flink)22%
United States54%
United Kingdom & EU19%
Canada11%
India & SE Asia9%
Australia, NZ, other7%
Series B to D, data & AI28%
Enterprise & non-tech20%
Late-stage product cos17%
FAANG & equivalent14%
Fintech & quant12%
Between roles, in-market9%
What this audience gives you
Three things this audience has that others don't
Earned attention
A placement here sits inside the work the engineer came to do. They are not scrolling; they are practicing. Your brand or your role lands at full attention.
In-market signal
Interview prep correlates with stack opinions and offer receptivity. You reach engineers who are choosing tools, choosing employers, and paying close attention to both.
Become a partner
The audience above is who you reach, on the surface they came here to use
Tell us what you have in mind and we'll scope it.
Research and guides
How buyers reach and hire this audience.
Channel-by-channel research on hiring and marketing to data, ML, and AI engineers in 2026. Updated monthly.
Hire
How to hire data engineers
Eight channels ranked. Cost-per-qualified-candidate, time-to-fill, and comp benchmarks.
Reach
How to market to data engineers
Twelve channels ranked by ROI. Six channels to skip. Six-month attribution framework.
Pillar
Developer marketing 2026
Channel taxonomy, budget benchmarks, and the DevRel-vs-marketing line.
Hire
How to hire ML engineers
The 25 to 40 percent MLOps premium and four interview blocks that separate notebook from production.
Hire
How to hire AI engineers
The LLM-era role profile, 15 to 25 percent premium over MLE, and OSS contributor sourcing.
Audience
Where data engineers hang out online
The 20+ communities mapped. dbt Slack, MLOps Community, Latent Space, r/dataengineering, and more.