Job Description
We’re searching for a
Data Engineer with deep Azure expertise to help power a growing enterprise’s digital transformation. You’ll work with modern Azure tools— Data Factory, Synapse, Databricks, Data Lake, and Azure SQL —to build large-scale, cloud-native data pipelines and infrastructure. This is a full-time opportunity to design the architecture that supports everything from business intelligence to advanced AI and RAG-based applications . This role is about more than just building data pipelines—it’s about solving hard problems at scale and working at the
intersection of data, AI, and business strategy . You’ll be part of a collaborative digital technology team, partnering closely with analysts, data scientists, and DevOps engineers to unlock smarter decisions. If you’re excited by the chance to lead Azure-driven data innovation, streamline performance, and help drive machine learning initiatives—this is your kind of challenge.
Contract Duration Required Skills & Experience - 3–5 years of professional data engineering experience
- Proven hands-on work with Azure Data Factory, Synapse, Databricks, Data Lake, and Azure SQL
- Strong SQL, Python, and/or Spark skills
- Experience building and managing robust ETL/ELT pipelines
- Familiarity with Azure RBAC, encryption, and regulatory frameworks like GDPR or HIPAA
- Experience with CI/CD, version control (Git), and tools like Azure DevOps
- Strong data modeling, transformation, and performance optimization skills
Desired Skills & Experience - Experience with real-time streaming (e.g., Event Hubs, Kafka, IoT Hub)
- Exposure to Azure ML, OpenAI, or other AI/ML frameworks
- Background in BI tools like Power BI or Tableau
- Familiarity with data governance, metadata management, and quality assurance
- Bonus points for experience in manufacturing or service industries
What You Will Be Doing Tech Breakdown
- 60% - Azure Data Factory, Synapse, Databricks, Data Lake, Azure SQL
- 20% - Azure DevOps, Git, Terraform, CI/CD pipelines
- 20% - BI and AI enablement, including integration with RAG and Azure ML
Daily Responsibilities
- 60% - Data pipeline development and cloud architecture
- 20% - Performance tuning, data governance, and security
- 20% - Collaboration with data scientists, DevOps, and business stakeholders
Posted By: Ben Farsolas
Job Tags
Full time, Contract work,