Cloud Data Engineer
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Summary
Dataflix is hiring a Cloud Data Engineer in San Francisco to design, build, and optimize scalable ETL/ELT pipelines and analytics-ready cloud data platforms using Snowflake, DBT, and Azure data services (Data Factory, Data Lake, Synapse), including data modeling, quality/governance, and CI/CD support.
Overview:
We are seeking a Cloud Data Development Engineer with strong
expertise in Snowflake, DBT, and Azure Data Services to design,
develop, and optimize modern cloud-based data solutions. The ideal
candidate will have hands-on experience building scalable data
pipelines, data transformation frameworks, and analytics-ready
data platforms. Experience in the Financial Services industry is
highly preferred.
Key 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.
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 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.
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 or
migration initiatives.