r/dataengineering for B2B sellers
482,777 members · rules and posts checked 17 October 2026
r/dataengineering is a data engineering community with 482,777 members. Sellers can take part, but promotion is tightly limited: each person or organization may self-promote once per month, and any affiliation has to be disclosed.
People here ask for practical data engineering solutions and examples. Recent requests include provisioning cloud sandbox accounts with controls, open-source examples for evaluating semantic-layer tooling, and tools for capturing and organizing work notes.
Self-promotion: allowed with limits
Self-promotion is allowed only once per month and applies across accounts tied to the same organization. Promotional content must clearly disclose any affiliation, use the required affiliate labeling, and opaque marketing, recruiting, solicitation, networking, or feedback-fishing posts are not allowed.
1Don't be a jerk
Be respectful and keep criticism constructive.
2Search the sub & wiki before asking a question
Search past posts and the wiki before asking questions.
3Keep it related to data engineering
Only post topics related to data engineering.
4Limit self-promotion posts/comments to once a month
Self-promotion is limited to once per month per person or organization.
5No shill/opaque marketing
If you promote something you are connected to, disclose the relationship and use the required affiliate labeling.
6No recruiting, solicitation, or networking posts
Do not post recruiting, solicitation, networking, referral, feedback-seeking, or similar promotional requests.
7No resume/CV, interview, or exam preparation questions
Do not post resume reviews or interview/exam preparation questions.
8No technical error/bug questions
Do not post technical error or bug troubleshooting questions.
9No AI generated content/text
AI-generated post content is not allowed.
10No low effort content
Low-effort posts without enough context are not allowed.
11All links are reviewed
Links are manually reviewed and attempts to bypass review are banned.
Summarised from the community's posted rules on 17 October 2026. Moderators change rules; read the current rules before you post.
What buyers ask for here
Sample requests from public posts, paraphrased and anonymised, found 17 October 2026.
- “Looking for a self-service solution that can provision temporary, isolated cloud sandbox accounts with spending, access, and time controls.”
- “Seeking an open-source, non-trivial example implementation for a metrics framework to evaluate semantic-layer tooling.”
- “Looking for AI tools that can capture voice or activity notes and help organize rapidly changing work tasks.”
Of 124 recent posts we checked, 2% read as someone looking to buy or hire. How we collect this
Who it suits
Good for
- Data engineering platforms and infrastructure
- Cloud data warehousing and lakehouse tools
- Data pipeline, orchestration, and ETL software
- Data governance, observability, and analytics engineering tools
Less useful for
- Recruiters and staffing services
- General networking or referral services
- Non-data-engineering products
How to take part without getting removed
- Keep posts and comments on data engineering topics.
- Be respectful, and keep criticism constructive.
- Search past posts and the wiki before asking a question.
- Self-promotion is limited to once per month across your whole organization.
- If you mention something you're connected to, disclose the relationship clearly and use the required affiliate labeling.
- Don't post recruiting, solicitation, networking, referral, feedback-seeking or similar promotional requests.
What a good reply looks like here
Good replies are specific and useful, and they answer the question that was asked. Help first and stay on data engineering. Mention your product only if the rules allow it and you disclose your affiliation.
Sample reply: For temporary, isolated cloud sandbox accounts, I would look for a self-service approach that supports automatic provisioning and teardown, spending controls, access controls, and time-based expiration. It also helps to check how permissions are managed, how usage is tracked, and whether sandbox environments can be standardized so teams get the same setup. Comparing options against those requirements should narrow the field.
When to skip r/dataengineering
This community is a poor fit if you're promoting recruiting, staffing, networking, referral or other solicitation-based services. It's also unlikely to be worth your time if your product has nothing to do with data engineering.
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