Data Engineer

Skillset: Snowflake, complex SQL queries, performance tuning, Python, Airflow, Data Modelling & proficiency in using AI

Key Responsibilities:

·         Develop and maintain data platform pipelines and data integration processes.

·         Support the implementation of conceptual, logical, and physical data models.

·         Build and maintain data transformations using dbt and contribute to scalable, reliable data solutions.

·         Collaborate with data engineers, data scientists, analysts, and cross-functional teams to deliver data products.

·         Apply data engineering concepts and technologies, including AWS services (S3, Lambda, SNS, SQS), Iceberg, Snowflake, dbt, and Airflow.

·         Participate in Agile/Scrum ceremonies and contribute to team planning and continuous improvement efforts.

·         Work with product managers, architects, and engineers to support the Core Data Platform roadmap.

·         Follow established standards and best practices for data pipelines, naming conventions, and platform development.

·         Monitor and support the quality, reliability, and operational health of data platform datasets and pipelines.

·         Contribute to documentation of data assets, processes, and platform standards.

·         Partner with stakeholders to understand business requirements and support delivery of data solutions.

·         Maintain documentation to support data quality, governance, and operational requirements.

Qualifications:

·         7+ years of experience developing and supporting data pipelines.

·         Understanding of data modeling concepts, including dimensional modeling and data normalization principles.

·         Proficiency in at least one program