
Chief Data Engineering Architect
2 weeks ago
This role involves the design, development, and maintenance of a modern data platform that supports analytics and reporting capabilities.
The ideal candidate will have deep technical expertise in ETL pipeline design, data modeling, and data infrastructure. They must be able to thrive in a fast-paced, engineering-driven environment.
Key responsibilities include designing and implementing efficient, scalable ETL/ELT pipelines and data flows, developing transformation models using dbt, and orchestrating pipelines via Airflow. Additionally, they must optimize large-scale processing jobs in Apache Spark, tune and manage relational and analytical databases (PostgreSQL, Snowflake), and maintain schemas using Star Schema, 3NF, and SCD2 methodologies.
Requirements:- Advanced proficiency in SQL and ETL/ELT design.
- Strong experience with dbt, Airflow, and Spark.
- Deep understanding of data modeling techniques (Star Schema, 3NF, SCD2).
- Proven ability to optimize and tune PostgreSQL and Snowflake for performance.
- Familiarity with lakehouse architecture principles and tools.
- Solid experience in data governance, validation frameworks, and pipeline monitoring.
- Strong grasp of GitFlow, CI/CD pipelines, and containerization (Docker/Ansible).
- Hands-on experience with cloud platforms (AWS, GCP, Azure).
- Familiarity with IaC tools and DevOps best practices.
- Experience working in regulated or enterprise environments with strict data governance policies.
The right candidate will have the opportunity to shape and scale a modern data platform in a collaborative, engineering-led environment where their voice matters.
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