Cyber Security

What are the most critical Cyber Security concerns for a Data Engineering team today?

TH Asked by Thomas Parker · 12-05-2025
0 upvotes 15,833 views 0 comments
The question

We are moving our on-prem data to a public cloud, and our security team is worried about "Data Exfiltration." In Data Engineering, how do we ensure that our pipelines are secure without killing our development velocity? Are things like VPC peering and service-linked roles enough, or do we need to implement granular field-level encryption for every single dataset we ingest?

3 answers

0
RE
Answered on 16-05-2025

Security shouldn't be an afterthought in Data Engineering; it needs to be part of the pipeline design. VPC peering and private endpoints are mandatory to ensure data never traverses the public internet. For sensitive info, you should implement "PII Masking" at the point of ingestion. Instead of encrypting everything—which makes querying a nightmare—use a "Data Vault" approach where sensitive fields are replaced with tokens. This allows your Data Engineering team to work with the data without actually seeing the private details. Also, make sure you are rotating your IAM keys and using short-lived credentials via OIDC to minimize the risk of a leak.

0
MI
Answered on 20-05-2025

Are you worried more about external hackers or "insider threats" from users with too much access to your Data Engineering environment?

TH 24-05-2025

It’s actually a mix of both, Michael. I’ve seen cases where a developer accidentally pushed a hard-coded API key to a public repo. For our Data Engineering transition, we are looking into automated secret scanning and strict RBAC (Role-Based Access Control). We want to make sure that even if someone gets into the system, they can't just run a SELECT * on our customer table and download everything. It’s a fine line between keeping things secure and making sure the data scientists can actually do their jobs without asking for permission every five minutes.

0
AN
Answered on 28-05-2025

I highly recommend using "Infrastructure as Code" (Terraform) for your Data Engineering setup. It makes security audits 10x easier and more repeatable.

RE 30-05-2025

Angela is right. When your Data Engineering infrastructure is defined in code, you can run security linters to catch misconfigurations before they ever go live in the cloud.

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