Cloud Data Platform Architect

Our promise to you:

Joining Advent Health is about being part of something bigger. It’s about belonging to a community that believes in the wholeness of each person, and serves to uplift others in body, mind and spirit. Advent Health is a place where you can thrive professionally, and grow spiritually, by Extending the Healing Ministry of Christ. Where you will be valued for who you are and the unique experiences you bring to our purpose-minded team.

All while understanding that together we are even better.

All the benefits and perks you need for you and your family:

• Benefits from Day One:
  Medical, Dental, Vision Insurance, Life Insurance, Disability Insurance

• Paid Time Off from Day One

• 403-B Retirement Plan

• 4 Weeks 100% Paid Parental Leave

• Career Development

• Whole Person Well-being Resources

• Mental Health Resources and Support

• Pet Benefits

Schedule:

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Job Description:

Designs, implements, tests, deploys, and supports data pipelines using Cloud infrastructure and Azure services. Develops scalable, repeatable, and maintainable serverless solutions using Azure Data Factory, Azure Functions, and Databricks. Adopts best practices for data ingestion and extraction from multiple sources like RDBMS, No

SQL, Files, Kafka, and Big Data tools. Creates and maintains SQL code as necessary as part of data pipelines. Gathers project requirements by meeting with stakeholders and various operational and business teams. Works with Cloud administrators to implement and support enterprise security standards in the Cloud data infrastructure. Proposes and builds monitoring tools with Cloud administrators to optimize performance and ensure high availability.

Collaborates with system and product teams to understand system requirements and necessary modifications to data flow, security, and retention. Creates solutions to improve product stability, scalability, and performance. Works with data warehouse, business intelligence, and advanced analytics teams to evaluate Big Data and cloud use cases. Escalates support issues with internal teams and vendors. Participates in rotational on-call duty to support the production environment.

Develops, manages, and owns the full data lifecycle from raw data acquisition through transformation to end-user consumption. Leads the evaluation and adoption of AI capabilities within the Cloud Data Platform, with a focus on improving data engineering productivity, Snowflake development practices, data quality, metadata management, and platform automation. Researches and enables Snowflake and Azure AI features such as Snowflake Cortex, Cortex Code Assistant, Cortex AI functions, Cortex Search, Cortex Analyst, and Azure AI services.

Establishes best practices and governance patterns to ensure AI is used appropriately, securely, and cost-effectively, while reinforcing strong data engineering principles such as data cleansing, curation, standardization, and reusable pipeline design.

Knowledge, Skills, and Abilities:

• See the big picture concerned data analytics landscape, tools, solutions, and business goals. [Required]
• Proficiency with SQL. [Required]
• Understanding of distributed computing paradigm and working knowledge in technologies like Spark, Impala, NiFi, Azure Data Factory, Azure Functions and Snowflake. [Required]
• Expert in managing code and dependencies, building and maintaining CI/CD pipelines in Azure Dev Ops/ Git Hub along with other Configuration management best practices. [Required]
• Ensure alignment with our Cloud Dev Ops model based on 100% automation and adoption of repeatable patterns that can be leveraged across the organization. [Required]
• Full stack design and development experience within the Azure ecosystem in combination with Snowflake including building platforms and frameworks to create consistent, verifiable, and automatic management of applications and infrastructure between non-production and production environments. [Required]
• Good understanding of Big Data technologies like Spark, NiFi, Impala, Sqoop, Hive and File formats like Parquet, AVRO, ORC, CSV, JSON.…