remote
Data Engineer - Kyndryl
Data Engineer
Design and maintain scalable data platforms, build robust ETL pipelines, and ensure high‑quality, accessible data for analytics and decision‑making using Python, SQL, and cloud services.
About the role
Key Responsibilities
- Design, develop, and optimize end‑to‑end data pipelines to ingest, transform, and load large‑scale datasets.
- Build and maintain data models and schemas that support reporting, analytics, and machine‑learning workloads.
- Implement data quality, validation, and monitoring frameworks to ensure reliable, trustworthy data.
- Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable data solutions.
- Leverage cloud services (e.g., AWS) for storage, processing, and orchestration of data workflows.
Requirements
- Strong proficiency in Python and SQL for data manipulation and scripting.
- Hands‑on experience building ETL pipelines using tools such as Apache Airflow, AWS Glue, or similar.
- Solid understanding of data modeling concepts and relational/NoSQL databases.
- Familiarity with cloud platforms (AWS preferred) and services like S3, Redshift, or Athena.
- Problem‑solving mindset with the ability to work independently and in cross‑functional teams.