Location: Las Vegas, NV
Salary: $70.00 USD Hourly - $80.00 USD Hourly
Description: We are seeking a Senior Azure Databricks Data Engineer to design, build, and optimize enterprise-scale data solutions that support analytics, operational reporting, and emerging AI initiatives. This role will be responsible for developing scalable ELT/ETL pipelines, modernizing legacy data environments, and delivering high-quality, cloud-native data products using Azure and Databricks technologies.
The ideal candidate combines strong hands-on expertise in Databricks, Spark, SQL, and Python with experience migrating legacy SQL-based workloads to modern cloud architectures. This individual will play a key role in advancing our enterprise data platform and enabling data-driven decision making across the organization.
Key Responsibilities- Design, develop, and maintain scalable ELT/ETL pipelines for enterprise analytics and operational reporting.
- Build and optimize data workflows using Databricks, Apache Spark, SQL, and Python.
- Ingest, transform, and integrate structured and semi-structured data from multiple enterprise systems.
- Develop and maintain Delta Lake tables and Medallion Architecture (Bronze, Silver, Gold) data models.
- Lead migration initiatives from legacy/on-premises SQL environments to Azure Databricks and cloud-native platforms.
- Implement data quality, monitoring, observability, and reliability best practices.
- Collaborate with business intelligence, analytics, and data science teams to deliver trusted and curated datasets.
- Support AI/ML and GenAI initiatives by preparing and structuring data for downstream applications, including LLM and RAG-based solutions.
- Troubleshoot and optimize large-scale Spark processing jobs for performance and cost efficiency.
- Document data pipelines, architecture designs, data flows, and operational procedures.
- Participate in code reviews and contribute to engineering standards, best practices, and governance processes.
- Support production deployments and ongoing operational excellence through CI/CD and DevOps practices.
Job Qualifications- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field, or equivalent experience.
- 5+ years of experience in Data Engineering, Data Platform Engineering, or related technical roles.
- Strong hands-on experience with:
- Azure Databricks
- Apache Spark
- SQL
- Python
- Experience designing and maintaining enterprise ETL/ELT pipelines.
- Experience with Delta Lake and Medallion Architecture frameworks.
- Proven experience migrating workloads from SQL Server or other legacy data platforms to cloud-based solutions.
- Experience with data orchestration tools such as:
- Azure Data Factory (ADF)
- Apache Airflow
- Databricks Workflows
- Strong understanding of data modeling, data warehousing, and large-scale data processing principles.
- Experience with Git-based source control and collaborative development workflows.
- Knowledge of CI/CD, DevOps, and automated deployment practices.
Preferred Qualifications- Experience with Azure cloud services including Data Factory, Data Lake Storage, Synapse, Azure Functions, and related services.
- Experience supporting analytics environments within:
- Gaming
- Hospitality
- FinTech
- Highly regulated industries
- Exposure to AI/ML pipelines and MLOps practices.
- Experience with:
- Vector databases
- Retrieval-Augmented Generation (RAG)
- Large Language Model (LLM) integrations
- Generative AI solutions
- Knowledge of data governance, security, compliance, and observability frameworks.
- Experience tuning Spark workloads for performance and scalability.
Technical Environment- Azure Cloud
- Azure Databricks
- Apache Spark
- Delta Lake
- SQL Server
- Python
- Azure Data Factory (ADF)
- Airflow
- Databricks Workflows
- Git
- CI/CD Pipelines
- DevOps Tools
- AI/ML & GenAI Data Platforms
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