Data Ingestion Engineer

Summary

Job Summary (List Format) Data Ingestion Engineer

• Design, implement, test, deploy, and support data pipelines using Azure cloud infrastructure and services (Data Factory, Azure Functions, Databricks).
• Develop scalable, repeatable, and maintainable serverless solutions for data ingestion and extraction from diverse sources (RDBMS, NoSQL, Files, Kafka, Big Data tools).
• Create and maintain SQL code as part of data pipelines.
• Gather project requirements through meetings with stakeholders, operational, and business teams.
• Collaborate with Cloud administrators to implement and support enterprise security standards.
• Propose and build monitoring tools to optimize performance and ensure high availability.
• Work with system and product teams to understand requirements and modify data flow, security, and retention as needed.
• Create solutions to improve product stability, scalability, and performance.
• Collaborate with data warehouse, BI, and analytics teams to evaluate Big Data and cloud use cases.
• Escalate support issues to internal teams and vendors when necessary.
• Participate in rotational on-call duty to support production environments.
• Manage the full data lifecycle from data acquisition through transformation to end-user consumption.
• Lead evaluation and adoption of AI capabilities within the cloud data platform (focus on Snowflake and Azure AI features).
• Establish best practices and governance for AI, ensuring secure, cost-effective, and high-quality data engineering.
• Research and enable new AI and cloud features (e.g., Snowflake Cortex, Azure AI services).
• Develop and maintain CI/CD pipelines and manage code/dependencies using Azure DevOps/GitHub.
• Ensure alignment with Cloud DevOps models based on automation and repeatable patterns.
• Provide technical expertise for complex projects and act as a business partner to other groups.
• Develop project plans including financials, resource management, and risk assessment.
• Present technical information to technical staff and leadership across the organization.
• Assist team members with production issues and communicate with stakeholders.
• Participate in the strategic development of modern data platforms for the organization.
• Adopt and enforce strong data engineering principles such as data cleansing, curation, standardization, and reusable pipeline design.

Minimum Qualifications

• Bachelor s degree in Computer Science, Data Science, or related field (Master s preferred).
• Minimum 10+ years of experience in software design/architecture with databases, big data, and cloud platforms.
• 5+ years programming experience (Java, Python, Scala).
• 3+ years experience with big data, Hadoop/distributed systems, Azure/AWS, and Snowflake.
• Proficiency with SQL, big data technologies (Spark, NiFi, Impala, Sqoop, Hive), and file formats (Parquet, AVRO, ORC, CSV, JSON).
• Experience with Infrastructure as Code (Terraform) for Azure resources.
• Experience in researching and synthesizing emerging tech trends and solutions.

Preferred Qualifications

• Experience with Snowflake Cortex, Databricks, Azure AI services.
• Understanding of healthcare industry data (HL7, Epic Data model).
• Knowledge of Azure networking concepts.
• Experience with Cloudera Hadoop or similar.
• Experience creating testing frameworks for pipelines, performance tuning, and Data Warehousing/BI.

Certifications (At Least One Required)

• Microsoft Certified: Fundamentals (Cloud, Azure, AI, Data, Security, etc.) Required
• SnowPro (Data Engineer/Architect), Hadoop/Big Data, Databricks certifications Preferred

Other Requirements

• Must be onsite 3x a week in Altamonte Springs, FL.
• No sponsorship available.
• Must complete onsite technical interview.