Cloud Development Engineer

Dataflix Inc.; San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Dataflix Inc. in San Francisco is seeking a Cloud Data Development Engineer to design, build, and optimize modern cloud data platforms using Snowflake, DBT, and Azure services.

You will develop scalable ETL/ELT pipelines, data models, and analytics-ready data for business insights. The ideal candidate will have 7-8 years of experience in data engineering, strong SQL and Python skills, and a solid understanding of data warehousing concepts and agile processes.

Qualifications

• 7-8 years of experience in Data Engineering and Cloud Data Development.
• Strong hands-on experience with Snowflake.
• Strong experience with DBT (Data Build Tool).
• Experience with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Synapse Analytics and other Azure services.
• Strong SQL development and performance tuning skills.
• Experience building and supporting ETL/ELT solutions.
• Working knowledge of Python for data engineering tasks.
• Understanding of data warehousing concepts, dimensional modeling, and data integration patterns.
• Experience with Agile development methodologies.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Snowflake, DBT, and Azure services.
• Build and optimize data models, data transformations, and data integration workflows.
• Develop and support cloud-native data solutions leveraging Azure Data Factory, Azure Data Lake, Azure Synapse, and related Azure services.
• Optimize Snowflake performance, data storage, and query efficiency.
• Collaborate with business stakeholders, data architects, and analytics teams to understand data requirements and deliver solutions.
• Implement data quality, validation, monitoring, and governance processes.
• Support CI/CD deployment activities and follow best practices for code management and automation.
• Troubleshoot production issues and ensure reliable data operations.

Skills

SQL development

Python

Data modeling

Data integration

Agile methodologies

Data quality

Data governance

CI/CD practices

Tools

Snowflake

DBT

Azure Data Factory

Azure Data Lake Storage

Azure Synapse Analytics

Job description

San Francisco, United States

We design, build, and run modern data platforms and AI-native systems that drive productivity, efficiency, and quality - while enabling businesses to move faster and adapt to change.

Job Description

Overview:

We are seeking a Cloud Data Development Engineer with strongexpertise in Snowflake, DBT, and Azure Data Services to design,develop, and optimize modern cloud-based data solutions. The idealcandidate will have hands‑on experience building scalable datapipelines, data transformation frameworks, and analytics-readydata platforms. Experience in the Financial Services industry ishighly preferred.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines usingSnowflake, DBT, and Azure services.
  
• Build and optimize data models, data transformations, and dataintegration workflows.
  
• Develop and support cloud-native data solutions leveragingAzure Data Factory, Azure Data Lake, Azure Synapse, and relatedAzure services.
  
• Optimize Snowflake performance, data storage, and query efficiency.
  
• Collaborate with business stakeholders, data architects, andanalytics teams to understand data requirements and deliver solutions.
  
• Implement data quality, validation, monitoring, and governance processes.
  
• Support CI/CD deployment activities and follow best practicesfor code management and automation.
  
• Troubleshoot production issues and ensure reliable data operations.
  

Requirements

• 7-8 years of experience in Data Engineering and Cloud Data Development.
  
• Strong hands‑on experience with Snowflake.
  
• Strong experience with DBT (Data Build Tool).
  
• Experience with Azure Data Factory (ADF), Azure Data LakeStorage (ADLS), Azure Synapse Analytics, and other Azure services.
  
• Strong SQL development and performance tuning skills.
  
• Experience building and supporting ETL/ELT solutions.
  
• Working knowledge of Python for data engineering tasks.
  
• Understanding of data warehousing concepts, dimensionalmodeling, and data integration patterns.
  
• Experience with Agile development methodologies.
  

Preferred Qualifications

• Financial Services or Banking domain experience.
  
• Experience with Databricks, PySpark, or Spark-based data processing.
  
• Exposure to DevOps/CI-CD practices and source control tools.
  
• Snowflake or Azure certifications are a plus.
  

Nice to Have

• Kafka or streaming data experience.
  
• Data governance and data quality implementation experience.
  
• Experience working in large-scale cloud modernization ormigration initiatives.