Data Engineer
Build the data infrastructure and pipelines that power analytics and machine learning.
Data Engineer
Data Engineers are the backbone of the modern data stack. They build and maintain the infrastructure that enables data scientists, analysts, and ML engineers to do their work. With the explosion of data volumes and the shift to real-time analytics, Data Engineers who can design scalable, reliable, and cost-effective data pipelines are in extremely high demand. The role combines software engineering skills with deep knowledge of data systems and cloud platforms.
Skills
LinkedIn Optimization
- 1
Share insights on data architecture and pipeline design
- 2
Post about modern data stack trends and best practices
- 3
Highlight experience with data quality and governance
- 4
Connect with Heads of Data and Analytics leaders
- 5
Showcase data infrastructure projects with scale metrics
CV & Resume
- 1
Quantify: "Built data pipeline processing 50TB daily with 99.9% uptime"
- 2
Detail experience with different data warehouses and lakes
- 3
Show ETL/ELT pipeline design and optimization
- 4
Include data quality and testing frameworks
- 5
Highlight cost optimization for data infrastructure
Outreach Strategy
- 1
Research their data stack and suggest improvements
- 2
Mention experience with tools they use (Snowflake, Databricks, etc.)
- 3
Share case studies of data pipeline optimization
- 4
Connect with data team members directly
- 5
Demonstrate understanding of their data challenges
Interview Prep
- 1
Prepare data modeling and schema design scenarios
- 2
Review distributed systems concepts for data processing
- 3
Practice SQL optimization and window functions
- 4
Have examples of pipeline reliability improvements
A day as Data Engineer
Monitor data pipeline health dashboards, debug failed jobs, design new data models, optimize Spark jobs for performance, collaborate with data scientists on feature engineering, review pull requests, work on data quality testing.
Career Path
Common mistakes
Only showing SQL without pipeline engineering skills
Not mentioning data quality and testing
Ignoring cloud platform experience
Not quantifying pipeline scale and reliability
Focusing only on batch without streaming experience
Essential tools
FAQ
Average salary for a Data Engineer?
The average salary for a Data Engineer in Europe ranges between 50K - 95K EUR. This varies by experience, location, and company type.
Key skills for a Data Engineer?
Main technical skills: SQL, Python, Spark, Airflow, Cloud Data Platforms. Soft skills like communication and teamwork are equally important.
Career path for a Data Engineer?
Typical path: Junior Data Engineer > Data Engineer > Senior Data Engineer > Staff Data Engineer > Data Architect > Head of Data Engineering > VP of Data.