Job Description

• Azure Databricks Architecture & Design :
  • Design, build, and optimize scalable, high-performance data pipelines and data lakes using Azure Databricks.
  • Architect and implement end-to-end analytics solutions leveraging Databricks and other Azure services (e.g., Azure Data Lake, Azure SQL, Azure Blob Storage).
  • Lead the design of cloud-based architectures using Azure Databricks for data processing, transformation, and reporting.
• Data Engineering & Integration :
  • Design and implement ETL/ELT processes to ingest, process, and transform data across various sources (structured and unstructured).
  • Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and develop data solutions.
  • Manage data integration workflows between Databricks and other platforms like Power BI, Azure SQL, Synapse, etc.
• Optimization & Performance Tuning :
  • Identify performance bottlenecks in Databricks environments and optimize clusters, queries, and code.
  • Continuously improve and scale data pipelines to accommodate growing data volumes and business needs.
• Collaboration & Leadership :
  • Mentor and guide junior engineers and team members in best practices related to Azure Databricks and data engineering.
  • Work closely with cross-functional teams (data science, analytics, business intelligence) to deliver integrated solutions.
  • Provide technical leadership in cloud data architecture and data engineering.
• Monitoring & Security :
  • Implement monitoring and alerting systems to ensure data pipelines and workflows are running smoothly.
  • Ensure compliance with data security and governance standards across the data ecosystem.
• Continuous Improvement & Innovation :
  • Stay up to date with the latest advancements in Azure Databricks, cloud technologies, and data engineering trends.
  • Continuously evaluate and introduce new technologies and methodologies to enhance the data platform.

• Experience :

  • Minimum 10 years of hands-on experience in data engineering and cloud-based data platforms.
  • At least 5 years of experience working with Azure Databricks, building data pipelines, and performing data engineering tasks.
  • Strong experience with Azure services such as Azure Data Lake, Azure Synapse Analytics, Azure Blob Storage, Azure SQL Database, etc.

• Technical Skills :

  • Proficiency in Spark, PySpark, Scala, or SQL for large-scale data processing.
  • Expertise in Databricks notebooks, clusters, job scheduling, and libraries.
  • Deep understanding of cloud-native data engineering practices and architecture on Azure.
  • Familiarity with data modeling, data lakes, and data warehouse concepts.
  • Expertise in Azure services: Data Factory, Data Lake, Synapse Analytics, Event Hubs, Cosmos DB.

• Data Pipeline and ETL/ELT Development :

  • Experience building and optimizing ETL/ELT workflows on Databricks.
  • Knowledge of data orchestration tools such as Azure Data Factory, Apache Airflow, or similar.

• Big Data Technologies :

  • Proficiency in handling large-scale distributed data processing with tools like Apache Spark.
  • Experience with technologies such as Kafka, Delta Lake, and Databricks Runtime.
  • Strong understanding of Delta Lake and Lakehouse architecture .

• Programming Languages :

  • Strong programming skills in Python, Scala, or Java.
  • Experience with SQL-based querying and optimizations.

• Cloud & DevOps :

  • Strong understanding of Azure cloud services and architecture.
  • Familiarity with DevOps principles, CI/CD pipelines, and automation tools. Terraform required.
  • Knowledge of Git, Azure DevOps, or similar version control and deployment systems.

• Collaboration & Leadership :

  • Excellent communication skills to work with both technical and non-technical stakeholders.
  • Proven track record of mentoring and leading teams of data engineers.
  • Experience managing complex projects and working with cross-functional teams.

• Certifications :

  • Microsoft Certified: Azure Data Engineer Associate or equivalent certification.
  • Databricks Certified Associate Developer for Apache Spark.

• Education :

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

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