~5mo ago

Azure Databricks Engineer (Dallas, TX)

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Quick Summary

Overview

function googleTranslateElementInit() { new google.translate.TranslateElement({pageLanguage: 'en'}, 'google_translate_element'); } Azure Databricks Engineer (Dallas, TX)

Key Responsibilities

Azure Databricks Architecture & Design: Design, build, and optimize scalable, high-performance data pipelines and data lakes using Azure Databricks.

Requirements Summary

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.

Technical Tools

airflowazurejavakafkapower-bipythonscalasparksqlterraformci-cddatabase-designetlmentoringperformance-optimization

Key Responsibilities:

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.

Required Skills and Qualifications:

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.

Preferred Qualifications:

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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