Lead Data Engineer

• Building and maintaining secure, high-performing data pipelines in Azure to support real-time, near-real-time, and batch workloads.
• Contributing to the design and development of a new Azure SQL transactional environment with strong performance, integrity, and concurrency standards.
• Applying advanced data modeling best practices to support both operational and analytical needs.
• Writing and optimizing complex SQL code, including stored procedures, functions, and performance-focused queries.
• Using Python for data transformations, automation, API connections, and custom Azure integrations.
• Implementing CI/CD processes for data pipelines, database changes, and infrastructure components using Azure DevOps and Git.
• Establishing and managing data quality controls, monitoring frameworks, and metadata standards across all pipelines.
• Supporting real-time integrations through API and event-driven patterns.
• Managing multiple Azure environments with consistent configuration and deployment workflows.
• Partnering with business and technical stakeholders to translate requirements into scalable data solutions.
• Monitoring performance, pipeline health, costs, and data freshness while proactively addressing issues.
• Participating in team Agile activities and providing technical guidance where needed.

Do you have experience in Technical writing?, * 7+ years in data engineering, with extensive experience using Azure data services.

• Advanced SQL expertise with a strong background in tuning, performance optimization, and complex database logic.
• Proficiency in Python for scripting, automation, and data processing.
• Strong understanding of dimensional modeling, warehousing concepts, and database architecture.
• Proven experience building large-scale Azure Data Factory pipelines and migrating data from legacy systems.
• Hands-on experience with CI/CD processes, DataOps principles, and Agile environments.
• Excellent communication, documentation, problem-solving, and cross-team collaboration skills.

Preferred Qualifications:

• Knowledge of Synapse, Data Lake, Databricks, and Azure event-based services.
• Experience using infrastructure-as-code tools like Bicep or Terraform.
• Familiarity with data quality and governance platforms.
• Background in migrating legacy systems to Azure-native platforms.
• Azure data engineering certifications (e.g., DP-203).
• Industry exposure in automotive services, insurance, or related fields is a plus.

If you or someone you know has the skills to build and optimize modern Azure data environments, we encourage you to apply today!