Professional Resume Template for
Azure Data Engineer
Elena M. Rostova
Seattle, WA
(206) 555-0142
elena.rostova@email.com
linkedin.com/in/elena-rostova | github.com/elenarostova | elenarostova.dev
Professional Summary
Systems-oriented Azure data engineer with 5 years of experience designing and optimizing cloud data architectures and enterprise pipelines. Expert in building scalable ELT workflows using Azure Data Factory, Azure Synapse, and Databricks. Successfully migrated 3 legacy on-premises databases to Azure Gen2 Data Lake, reducing data processing latency by 35% and cloud storage costs by $140,000 annually. Proficient in PySpark, SQL, and Terraform for Infrastructure as Code (IaC) deployment. Proven ability to collaborate with data science teams to optimize feature stores and machine learning deployment pipelines.
Work Experience
Azure Data Engineer — CloudScale Technologies
Seattle, WA | January 2024 – Present
- Architected and deployed 14 enterprise-scale ETL pipelines using Azure Data Factory, migrating 40TB of legacy warehouse data to Azure Synapse, which accelerated analytics dashboard queries by 45%.
- Designed PySpark transformations in Azure Databricks that processed 12M daily events, resolving pipeline congestion issues to reduce hourly data ingestion failure rates from 4.8% to under 0.2%.
- Implemented infrastructure as code using Terraform to deploy Azure Cosmos DB and SQL instances, cutting resource setup time by 80% and saving $45,000 in yearly infrastructure over-provisioning.
- Partnered with security teams to enforce Azure Key Vault integration and column-level encryption across 8 primary databases, achieving 100% compliance with HIPAA data protection standards.
Associate Data Engineer — Apex Data Services
Seattle, WA | June 2021 – December 2023
- Built and maintained 8 data pipeline integrations using SQL and Python, transferring 5TB of customer telemetry data into Azure Data Lake Storage Gen2, increasing dashboard refresh speed by 28%.
- Optimized SQL query performance across 3 active Azure SQL Database instances by refactoring indexing strategies, saving 14 server hours weekly and reducing query runtimes by an average of 32%.
- Automated pipeline status monitoring by writing Python alerts triggered by Azure Monitor alerts, cutting average incident response and resolution time from 4 hours down to 18 minutes.
- Collaborated with business intelligence analysts to construct 6 star-schema data models in Azure Synapse, reducing report generation times for executive stakeholders by 25% over 6 months.
Education
Bachelor of Science in Computer Science
University of Washington · Seattle, WA · 2021
Skills
Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure Data Lake Storage Gen2, PySpark, Python, SQL, ETL/ELT pipelines, Apache Spark, Terraform, Azure Cosmos DB, Azure Event Hubs, Data modeling, Star schemas, CI/CD, Azure DevOps, Azure Monitor, Azure Key Vault
Projects
Real-Time Telemetry Pipeline
Role: Lead Data Engineer
Tools: Azure Event Hubs, Azure Stream Analytics, Azure Databricks, Power BI
Built a streaming data pipeline handling 5M daily events, enabling real-time IoT dashboards, reducing analytics latency from 15 minutes to 4 seconds, and cutting alert delays by 90%.
Data Lakehouse Migration
Role: Azure Data Engineer
Tools: Azure Data Factory, PySpark, Delta Lake, Terraform, Git
Spearheaded migration of 15 legacy databases to a Delta Lake structure on ADLS Gen2, decreasing query execute times by 38% and lowering annual compute costs by $62,000.
Certifications
- Microsoft Certified: Azure Data Engineer Associate (DP-203) (2023)
- Databricks Certified Associate Developer for Apache Spark (2024)
Additional information
- Languages: English (Native), Russian (Conversational)
- Volunteer Work: Technical mentor for local women-in-tech coding bootcamps (2023-present)
- Availability: 2 weeks notice
Job Market Insights
Market data and opportunities for
Azure Data Engineer
Job Market Insights
$115,000
-
$165,000
Avg:
$135,000
Growth Outlook:
The demand for skilled Azure Data Engineers in the United States is projected to grow significantly as organizations expand their cloud infrastructures and integrate generative AI systems. Data engineers are crucial for building the pipelines that feed machine learning models and analytics dashboards. With the rapid adoption of cloud-native analytics platforms, job openings for cloud data specialists are forecasted to rise by 17% over the next decade, much faster than the average for all occupations. The transition to hybrid and multi-cloud architectures will drive long-term employment.
17% growth over 10 years
Key Skills Required
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