Back
Common data-engineer title, metro locations, mid-level experience and broad skillset drive high competition.
Core data engineering skills like Python, Airflow, and SQL are highly transferable across industries.
Explicit 5+ years plus mandatory Airflow, Python, and complex SQL increase screening strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain scalable ETL and data ingestion pipelines using Python and Apache Airflow.
Implement modular, microservices-based data platforms and REST APIs with validation and error handling.
Monitor, troubleshoot, and optimize pipeline performance and system logs using Splunk and other tools.
5+ years of work experience in data engineering or related roles.
Strong programming skills in Python and hands-on experience with Apache Airflow (DAG creation, scheduling, monitoring).
Proficiency in SQL and experience with RDBMS, e.g., Snowflake, PostgreSQL, MySQL.
Experience with data ingestion frameworks, REST API development, microservices architecture, and Splunk log analysis.
Experienced in building production-grade, scalable, modular data pipelines in fast-paced environments.
Familiar with data governance and metadata management platforms (e.g., Open-metadata, Alation, Collibra, DataHub).
Demonstrates expertise in system performance tuning and cross-functional collaboration for data quality and reliability.