Flexon Technologies Inc.

Azure Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Azure Data Engineer in Tampa, FL, with a contract length of "unknown." The pay rate is "unknown." Key skills include Python, SQL, Azure Databricks, Snowflake, and experience with data pipelines and ETL processes.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 6, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Tampa, FL
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🧠 - Skills detailed
#Python #PySpark #Data Pipeline #Batch #SQL (Structured Query Language) #Data Science #Cloud #Databricks #Snowflake #Data Architecture #Scala #Compliance #NoSQL #Azure cloud #"ETL (Extract #Transform #Load)" #Spark (Apache Spark) #Azure Databricks #Data Quality #Data Engineering #Databases #MongoDB #Azure
Role description
Job Title: Azure Data Engineer Location: Tampa, FL (On-Site) Job Description: We are looking for a proficient Azure Data Engineer to design, build, and maintain scalable data pipelines and architectures on the Azure cloud platform. The ideal candidate will have hands-on experience with data engineering tools and technologies including Python, SQL, Postgres, MongoDB, PySpark, Databricks, and Snowflake. You will collaborate with data scientists, analysts, and business stakeholders to deliver high-quality, performant data solutions that enable data-driven decision-making. Key Responsibilities: Design, develop, and optimize end-to-end data pipelines and ETL/ELT processes leveraging Azure Data services and frameworks. Build scalable data solutions using Azure Databricks, PySpark, and Snowflake to process both batch and real-time workloads. Develop and maintain data models and schemas in relational and NoSQL databases such as Postgres and MongoDB. Write efficient, reusable, and maintainable code primarily in Python and SQL to transform and load data across various systems. Collaborate with cross-functional teams including data scientists, analysts, and business users to gather requirements and deliver data solutions that meet business needs. Monitor data pipeline performance and implement improvements for reliability, scalability, and optimization. Ensure data quality, governance, and compliance across all data engineering efforts. Troubleshoot and resolve data-related issues, working closely with cloud infrastructure and platform teams. Document data architecture, workflows, and processes to support ongoing maintenance and knowledge sharing.