Azure Data Engineer Associate

Class Valuation, LLC
Milpitas, CA, United States
10 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$149,760.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Amazon Web Services Microsoft Azure Batch Processing Business Intelligence Development Big Data Cloud Database Cloud Storage Data Architecture Information Engineering Data Governance Extract Transform Load (ETL)
+31 more
Data Transformation Data Systems Data Warehousing Relational Databases DevOps Github Apache Hive Python (Programming Language) Key Management Scrum Methodology Standard Sql Azure Data Lake Data Streaming Azure Service Bus Google Cloud Cloud Platform System Azure Data Factory Apache Spark Git Data Lakes Pyspark Information Technology Deployment Automation Apache Kafka Machine Learning Operations Terraform Azure Synapse Analytics Stream Analytics Software Version Control Data Pipelines Databricks

Job description

We are looking for a skilled Databricks Engineer with strong expertise in designing, developing, and optimizing modern data engineering solutions on the Databricks Lakehouse Platform. The ideal candidate should have experience building scalable ETL/ELT pipelines, working with large-scale data, and leveraging Apache Spark to deliver high-performance data solutions., * Design, develop, and maintain scalable data pipelines using Databricks.

  • Build ETL/ELT workflows for batch and streaming data processing.
  • Develop solutions using PySpark, Spark SQL, and Delta Lake.
  • Implement Medallion Architecture (Bronze, Silver, Gold) for data transformation.
  • Integrate data from various sources including relational databases, APIs, cloud storage, and streaming platforms.
  • Optimize Spark jobs for performance, scalability, and cost efficiency.
  • Collaborate with Data Architects, Data Scientists, BI developers, and business stakeholders.
  • Implement CI/CD pipelines and deployment automation for Databricks workloads.
  • Ensure data quality, security, governance, and compliance.
  • Monitor, troubleshoot, and optimize production data pipelines.
  • Document technical solutions and follow engineering best practices., * Databricks
  • PySpark
  • Spark SQL
  • Delta Lake
  • Python
  • SQL
  • Azure/AWS/Google Cloud Platform (at least one cloud platform)
  • ETL/ELT Development
  • Data Lake Architecture

Nice to Have

  • Unity Catalog
  • Delta Live Tables (DLT)
  • MLflow
  • Kafka/Event Hubs
  • Azure Data Factory
  • Terraform
  • Azure DevOps/GitHub Actions

Requirements

Core Technologies

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

Cloud Platforms (one or more)

  • Microsoft Azure (preferred)
  • AWS
  • Google Cloud Platform

Azure Technologies (Preferred)

  • Azure Data Factory (ADF)
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure Synapse Analytics
  • Azure Key Vault
  • Azure DevOps

Data Engineering

  • Data Warehousing
  • Data Modeling
  • ETL/ELT Development
  • Batch Processing
  • Streaming (Kafka/Event Hubs)
  • Data Lake Architecture

DevOps & Version Control

  • Git
  • Azure DevOps / GitHub
  • CI/CD Pipelines

Preferred Qualifications

  • Experience with Unity Catalog.
  • Knowledge of Databricks Workflows and Jobs.
  • Hands-on experience with Delta Live Tables (DLT).
  • Exposure to MLflow is an added advantage.
  • Experience with data governance and security best practices.
  • Familiarity with Infrastructure as Code (Terraform) is a plus.

Educational Qualification

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

Preferred Certifications

  • Databricks Certified Data Engineer Associate
  • Databricks Certified Data Engineer Professional
  • Microsoft Certified: Azure Data Engineer Associate (DP-203)
  • Azure Fundamentals (AZ-900)

Good to Have

  • Experience with real-time analytics.
  • Knowledge of Lakehouse architecture.
  • Experience with Agile/Scrum methodologies.
  • Strong analytical and problem-solving skills.
  • Excellent communication and stakeholder management abilities.

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