Senior Data Engineer AI-Ready Cloud Pipelines Leader

Ah; United States; On-site; USD 97,000 - 181,000; Full time

Job summary

AdventHealth is seeking a data analytics professional to support consumer-facing digital products, focusing on data pipelines, AI readiness, and governed data workflows. You will contribute to reliable, scalable Cloud Data environments and BI tooling.

You will assemble large datasets, optimize SQL, translate EMR data, and build reusable data models while mentoring teammates and ensuring data quality and compliance.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 2+ years building data pipelines with Snowflake; Azure Data Factory familiarity.
• 3+ years in data engineering with SQL scripting and programming languages.
• Experience with Hadoop, Spark, Kafka.
• Strong analytical, problem-solving and communication skills.
• Knowledge of regulatory and transplant-related domains.

Responsibilities

• Assemble large, complex data sets from operational and cloud sources.
• Optimize SQL query performance with Enterprise Data Services and Cloud Data teams.
• Develop statistical analytics to identify patterns.
• Translate business logic from EMR databases into conformed datasets.
• Develop and enforce SOPs for data management.
• Design workflows in Alteryx for BI reporting to migrate datasets to the Cloud Data platform.
• Provide training and mentorship to team members on technical data skills.
• Ensure data quality and end-to-end data validation.

Skills

SQL

Python

Snowflake

dbt modeling

Alteryx

BI tools

Data analysis

Team leadership

Communication

PDSA

Education

Bachelor's degree

Tools

Azure Data Factory

Hadoop

Spark

HiveQL

Salesforce SOQL

Tableau

QlikView

Crystal Reports

Job description

AdventHealth is seeking a data analytics professional to support consumer-facing digital products, focusing on data pipelines, AI readiness, and governed data workflows. You will contribute to reliable, scalable Cloud Data environments and BI tooling.

You will assemble large datasets, optimize SQL, translate EMR data, and build reusable data models while mentoring teammates and ensuring data quality and compliance.