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Tech Stack
Tools & technologiesAzureCloudETLPythonScalaSQL
About the role
Key responsibilities & impact- Lead the design, development, and implementation of scalable data pipelines and infrastructure using Azure Databricks, Azure Data Factory, SQL Server, Salesforce integrations, and related technologies
- Develop and maintain both OLTP and dimensional data models based on business requirements, applying Kimball and Inmon methodologies as appropriate
- Optimize data storage and retrieval performance across SQL Server and cloud data platforms
- Integrate data from Salesforce and other SaaS applications via APIs and extraction workflows
- Implement and maintain batch and real-time data processing architectures
- Participate in code and architecture reviews to ensure adherence to data engineering standards and best practices
- Analyze and troubleshoot data pipeline and performance issues, providing timely and effective solutions
- Contribute to the continuous improvement of data engineering practices, tools, and processes
- Stay current with emerging trends in cloud data platforms and identify opportunities for innovation
- Champion comprehensive documentation of data architecture, lineage, and modeling decisions
- Facilitate knowledge sharing and mentorship across the team; engage cross-functionally to align on architectural vision
- Drive adoption of best practices including data governance, quality, security, and compliance standards
- Lead initiatives to reduce technical debt and improve pipeline performance and cost efficiency.
Requirements
What you’ll need- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
- At least five (5) years of experience in data engineering or a related field
- Three (3) or more years of hands-on experience with Azure cloud services including Azure Databricks, Azure Data Factory, and Azure Data Lake
- Two (2) or more years of specific experience with the Databricks platform, including ETL/ELT pipeline development, cluster management, and data workflow implementation
- Advanced proficiency with SQL Server including database administration, performance tuning, and stored procedures
- Strong proficiency in Python and/or Scala for data processing and automation
- Demonstrated expertise in conceptual, logical, and physical data modeling including star schema, snowflake schema, SCD Types 1/2/3, and medallion architecture patterns
- Experience with Salesforce data architecture and API-based data extraction
- Proficiency with Git workflows and CI/CD pipeline development
- Strong understanding of data engineering principles, data quality, and best practices.
Benefits
Comp & perks- Flexible work arrangements
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Data Pipeline DevelopmentETL/ELT DevelopmentDatabase AdministrationPerformance TuningData Workflow ImplementationData QualityData GovernanceAPI IntegrationData ArchitectureCloud Data Platforms
Soft Skills
MentorshipKnowledge SharingCross-Functional Collaboration
