Description

You will lead the design and implementation of complex data architectures and large-scale data pipelines.

Responsibilities

• Lead the development of data architectures and pipelines designed to handle large-scale datasets.
• Design, construct, and test data architectures that align with specific business requirements.
• Provide technical leadership for data projects to ensure high-quality solutions and adherence to best practices.
• Collaborate with product, finance, and other business units to ensure pipeline accuracy.
• Transform raw data into actionable insights using DBT.

Required Skills

• 8+ years of overall IT experience with at least 5 years focused on data engineering.
• Strong proficiency in Python scripting and PySpark for data processing.
• Advanced SQL skills and experience managing big data via Informatica ETL.
• Experience with data quality and optimization of data lakes in Iceberg format.
• Hands-on experience with AWS services including S3, Redshift, Lambda, EMR, Airflow, Postgres, SNS, and EventBridge.
• Expertise in Bash/Shell scripting.
• Experience using Data Build Tool (DBT) or similar transformation tools.
• Experience with MuleSoft API.
• Background working in Agile environments.

Preferred Skills

• Experience with Kafka and Tableau.
• Strong understanding of healthcare data systems.
• Experience leading data engineering teams.

Key Skills

Education

Any Graduate