Senior Data Engineer to $6000

Job Description

• Solid experience with the Azure data ecosystem: Data Factory, ADLS Gen2, Azure SQL, Blob Storage, Key Vault, and Functions
• Proficiency in Python and SQL for building ingestion, transformation, and processing workflows
• Clear understanding of Lakehouse architecture principles, Delta Lake patterns, and modern data warehousing
• Practical experience building config-driven ETL/ELT pipelines, including API integrations and Change Data Capture (CDC)
• Working knowledge of relational databases (MS SQL, PostgreSQL) and exposure to NoSQL concepts
• Ability to design data models and schemas optimized for analytics and reporting workloads
• Comfortable working with common data formats: JSON, Parquet, CSV
• Experience with CI/CD automation for data workflows (GitHub Actions, Azure DevOps, or similar)
• Familiarity with data governance practices: lineage tracking, access control, encryption
• Strong problem-solving mindset with attention to detail

• Clear written and verbal communication for async collaboration

   

Nice-to-Have

• Experience with Azure Databricks (Delta Live Tables, Unity Catalog, Time Travel)
• Proficiency with Apache Spark using PySpark for large-scale data processing
• Experience with Azure Service Bus/Event Hub for event-driven architectures
• Familiarity with machine learning and AI integration within data platform context (RAG, vector search, Azure AI Search)
• Data quality frameworks (Great Expectations, dbt tests)

• Experience with Power BI semantic models and Row-Level Security

   

Job Responsibilities

• Design, implement, and optimize scalable and reliable data pipelines using Azure Data Factory, Synapse, and Azure data services
• Develop and maintain config-driven ETL/ELT solutions for batch and API-based data ingestion
• Build Medallion architecture layers (Bronze → Silver → Gold) ensuring efficient, reliable, and performant data processing
• Ensure data governance, lineage, and compliance using Azure Key Vault and proper access controls
• Collaborate with developers and business analysts to deliver trusted datasets for reporting, analytics, and AI/ML use cases
• Design and maintain data models and schemas optimized for analytical and operational workloads
• Implement cross-system identity resolution (global IDs, customer/property keys across 8+ platforms)
• Identify and resolve performance bottlenecks, ensuring cost efficiency and maintainability of data workflows
• Participate in architecture discussions, backlog refinement, and sprint planning
• Contribute to defining and maintaining best practices, coding standards, and quality guidelines for data engineering
• Perform code reviews and foster knowledge sharing within the team

• Continuously evaluate and enhance data engineering tools, frameworks, and processes in the Azure environment

   

Why TeamCraft?

• Greenfield project - build architecture from scratch, no legacy debt
• Direct impact - your pipelines power real AI products and business decisions
• Small team, big ownership - no bureaucracy, fast iteration, your voice matters
• Stable foundation - US-based company, 300+ employees
• Growth trajectory - scaling with technology as the driver

About the Project

TeamCraft is a large U.S. commercial roofing company undergoing an ambitious AI transformation. We’re building a centralized data platform from scratch - a unified Azure Lakehouse that integrates multiple operational systems into a single source of truth (Bronze -> Silver -> Gold).

This is greenfield development with real business outcomes - not legacy maintenance.