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.
Fähigkeiten
LinkedIn-Optimierung
- 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
Lebenslauf
- 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-Strategie
- 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-Vorbereitung
- 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
Ein Tag als 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.
Karrierepfad
Häufige Fehler
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
Wichtige Tools
Häufig gestellte Fragen
Durchschnittsgehalt für eine/n Data Engineer?
Das Durchschnittsgehalt für eine/n Data Engineer in Europa liegt zwischen 50K - 95K EUR. Dies variiert je nach Erfahrung, Standort und Unternehmenstyp.
Kernkompetenzen für eine/n Data Engineer?
Wichtigste technische Fähigkeiten: SQL, Python, Spark, Airflow, Cloud Data Platforms. Soft Skills wie Kommunikation und Teamarbeit sind ebenso wichtig.
Karrierepfad für eine/n Data Engineer?
Typischer Weg: Junior Data Engineer > Data Engineer > Senior Data Engineer > Staff Data Engineer > Data Architect > Head of Data Engineering > VP of Data.
Data Engineer
Reiche dein Profil zur Prüfung ein. Ich studiere jede Bewerbung persönlich. Wenn du qualifizierst, kontaktiere ich dich mit einer detaillierten Analyse und deinem personalisierten Optimierungsplan.