AWS DE

Job Requirements
JD: Skill - Data-Other ELT/ETL Tools
Competency Group
DATA-Data Engineering
Position summary
The Data Engineer is a strong individual contributor responsible for designing, building, and owning the data pipelines and transformation layer that power our Enterprise Data platform.
You'll work closely with data architects, analysts, and cross-functional teams to deliver reliable, well-governed data across its full life cycle—from ingestion through to analytics-ready, trusted datasets.
Key responsibilities -Design, build, and maintain scalable ETL/ELT pipelines using Python and Apache Airflow.
Own the dbt Core transformation layer, including models, tests, documentation, and deployment.
Manage the full data life cycle across ingestion, transformation, quality, storage, and retention.
Define data management standards for data quality, cataloging, and lineage.
Administer and optimize the Airflow environment, including Cloud Composer where applicable.
Collaborate with data architects, analysts, and cross-functional teams to deliver reliable data pipelines.
Conduct design and code reviews.
Mentor junior data engineers.
Troubleshoot and resolve production data pipeline issues.
Required qualifications -4+ years of experience in data engineering.
Strong experience with: Python, Apache Airflow, ETL/ELT pipeline architecture, dbt Core
Strong understanding of data management principles and the end-to-end data life cycle.
Experience with SQL and relational or cloud data warehouse platforms.
Experience with Git-based workflows and CI/CD for data pipelines.
Understanding of Agile development methodologies.
Experience writing automated tests for data pipelines and dbt models.
Preferred Qualifications -Experience With Google Cloud Platform (GCP).
Experience with Google Cloud Storage (GCS).
Experience with Cloud Composer.
Work Experience
Experience with Kafka or other event-driven data streaming tools
7-10Years

Work arrangement
No