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Senior Azure Databricks Data Engineer

  • NY, United States

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The original listing is kept below for reference.

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Original job description

Archived listing. The details below describe a past opening.

Job Summary We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives. Job Description: Azure / Databricks Data Engineer (9-15 Years Experience) Senior Azure Databricks Data Engineer Experience 9-15 Years of IT Experience Location Hybrid

Job Summary We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.

Key Responsibilities

  • Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services.
  • Build and optimize ETL/ELT workflows for large-scale structured and unstructured data.
  • Develop data models and implement data quality, validation, and governance frameworks.
  • Integrate data from multiple sources into a unified Lakehouse architecture.
  • Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency.
  • Implement security controls, access management, and data governance using Unity Catalog.
  • Collaborate with business, analytics, and AI/ML teams to deliver trusted data products.
  • Monitor, troubleshoot, and resolve data pipeline issues.
  • Support CI/CD, DevOps, and infrastructure automation practices.
  • Maintain technical documentation and best practices.

Required Technical Skills Core Technologies

  • Databricks Lakehouse Platform
  • Apache Spark / PySpark
  • Delta Lake
  • SQL
  • Python

Data Engineering

  • ETL / ELT Development
  • Data Modeling
  • Data Warehousing
  • Data Quality & Validation
  • Streaming & Real-Time Processing

Governance & Security

  • Unity Catalog
  • Data Lineage
  • Row-Level Security
  • Access Control & Compliance
  • Data Governance Frameworks

Cloud & DevOps

  • Azure / AWS / GCP
  • Terraform
  • GitHub Actions / Azure DevOps
  • CI/CD Pipelines

Analytics & AI

  • Semantic Layers
  • Data Products
  • BI Platforms
  • Machine Learning Support
  • Generative AI & RAG Architectures

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
  • 9-15 years of experience in Data Engineering and Data Warehousing.
  • Minimum 5+ years of hands-on experience with Azure Data Engineering technologies.
  • Minimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem.
  • Strong understanding of data lake, lakehouse, and cloud-native architecture patterns.
  • Experience in handling large-scale structured and unstructured datasets.
  • Strong analytical, problem-solving, and troubleshooting skills.

Preferred Qualifications

  • Microsoft Certified: Azure Data Engineer Associate (DP-203).
  • Databricks Certified Data Engineer Associate/Professional.
  • Experience with Snowflake, Power BI, or Microsoft Fabric.
  • Experience in real-time streaming solutions using Kafka/Event Hubs.
  • Exposure to Data Governance and Master Data Management initiatives.

Soft Skills

  • Strong stakeholder management and communication skills.
  • Ability to lead technical initiatives and drive architecture discussions.
  • Experience working in Agile/Scrum environments.
  • Excellent documentation and presentation skills.
  • Strong mentoring and team leadership abilities.

Nice to Have

  • Microsoft Fabric
  • Power BI
  • Azure Event Hubs
  • Kafka
  • Machine Learning data pipelines
  • Data Governance tools such as Purview

Support critical and nonproduction databases in multitenant, highstress environments. Support applications Installation, Configuration, Management, and Monitoring of databases in a SOX and PHI compliant environment Installation, configuration, and integration of thirdparty applications and tools Development of procedures for automated monitoring and proactive intervention, preventing customer impact Bachelors Degree/ Post Bachelor Degree 8 - 10+ Years

More about this job

Skills

  • Microsoft Azure
  • Databricks
  • Data engineering
  • Cloud technologies
  • Process data
  • Apache Spark
  • Unstructured data
  • Data models
  • Unity
  • ML
  • Troubleshoot
  • CI/CD
  • DevOps
  • Documentation
  • PySpark
  • SQL
  • Python
  • Data modelling
  • Data warehousing
  • Microsoft Access
  • Regulatory compliance
  • AWS
  • Google Cloud
  • IBM Terraform
  • GitHub
  • Google Analytics
  • Machine learning
  • Computer science
  • Computer technology
  • Problem solving
  • Troubleshooting
  • DP
  • Snowflake
  • Microsoft Power BI
  • Apache Kafka
  • Data management
  • Stakeholder management
  • Communication skills
  • Agile
  • Scrum

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