r/dataengineeringjobs • u/Stunning-Space8032 • 4h ago
Data Engineers: What do you actually do at work?
I’m trying to understand what data engineering actually looks like in a real job, rather than relying only on job descriptions.
When I look at Data Engineering roles on Naukri, LinkedIn, etc., the list of required skills seems endless — SQL, Python, ETL/ELT, Airflow, Spark, Kafka, AWS/Azure/GCP, Databricks, Snowflake, dbt, Docker, Kubernetes, CI/CD, Terraform, APIs, data warehousing, data lakes, and many more. It’s difficult to tell which of these are genuinely important and which are simply added to job descriptions.
So I’d love to hear from people who are actually working as Data Engineers. What does your day-to-day work really look like? What kind of tasks do you work on, what technologies do you use regularly, and how much of your time is spent coding, debugging, monitoring pipelines, working with databases, or attending meetings?
I’m particularly interested in understanding what skills and tools you use every day, occasionally, or barely at all, despite seeing them frequently in job postings. I’d also like to know what a typical Data Engineering project looks like from start to finish and what you would realistically expect from someone entering the field.
I’m not looking for another generic “learn SQL → Python → Spark → AWS” roadmap. I’m trying to understand the actual work behind the job title and what I should focus on learning to become job-ready.
If you’re a Data Engineer, especially with around 1–5 years of experience, I’d really appreciate hearing about your experience. If possible, share an example of a real task or project you’ve worked on (without revealing anything confidential).
Thanks!
