Experience: 10+ years, Python, SQL, Azure, Databricks
Job Description & Details
"Data engineering is exploding as companies race to turn raw data into actionable insights, and platforms like Databricks are at the heart of that transformation. A Senior Application Developer who masters Databricks and Azure can shape the future of lakehouse architectures for high\u2011impact businesses. This role in Pittsburgh offers a hands\u2011on opportunity to lead scalable data pipelines on a fully onsite basis.\n\n# Job Summary\nThe Senior Application Developer will design, build, and optimize end\u2011to\u2011end data pipelines on Databricks, implement lakehouse architecture, and integrate Azure services. The role demands deep expertise in Python, SQL, and modern data modeling (Kimball) while collaborating with cross\u2011functional teams to deliver high\u2011performance, data\u2011driven solutions.\n\n# Top 3 Critical Skills Table\n| Skill | Why it's critical | Mastery Level |\n|---|---|---|\n| Databricks (advanced) | Core engine for building and optimizing lakehouse pipelines | Senior |\n| Azure & Microsoft Fabric | Provides the cloud infrastructure and services for data processing | Senior |\n| Data Lakehouse Architecture | Enables unified storage & analytics, reducing latency and cost | Senior |\n\n# Interview Preparation\n1. **How do you design a scalable data pipeline in Databricks?**\n *What the interviewer is looking for:* Understanding of cluster sizing, job orchestration, fault tolerance, and performance tuning.\n2. **Explain the differences between traditional data warehouses and lakehouse architecture.**\n *What the interviewer is looking for:* Knowledge of storage layers, ACID compliance, and how lakehouse merges analytics and BI workloads.\n3. **Describe how you would implement Kimball dimensional modeling in a lakehouse environment.**\n *What the interviewer is looking for:* Ability to translate star/snowflake schemas to Delta Lake tables and maintain conformed dimensions.\n4. **What Azure services would you integrate with Databricks for a full data solution?**\n *What the interviewer is looking for:* Familiarity with Azure Data Lake Storage, Azure Synapse, Azure Key Vault, and Azure DevOps for CI/CD.\n5. **How do you monitor and optimize performance of SQL queries on Delta tables?**\n *What the interviewer is looking for:* Experience with query plan analysis, caching, Z\u2011ordering, and data skipping techniques.\n\n# Resume Optimization\n- Senior Application Developer\n- Databricks\n- Azure\n- Python\n- SQL\n- Data Lakehouse\n- Kimball data model\n- Microsoft Fabric\n- Data modeling\n- C2C\n\n# Application Strategy\nWhen reaching out to the recruiter, send a concise email that greets the hiring manager, briefly introduces yourself, and attaches your resume. Clearly highlight your top skills\u2014such as advanced Databricks development, Azure integration, and lakehouse architecture\u2014and reference specific projects where you delivered scalable data pipelines. Make sure to map your experience directly to the key responsibilities listed in the job description.\n\n# Career Roadmap\n| Current Role | Typical Experience | Core Focus | Next Position |\n|---|---|---|---|\n| Senior Application Developer | 10+ years | Build & optimize Databricks pipelines, lakehouse design | Lead Application Developer |\n| Lead Application Developer | 12\u201115 years | Lead teams, architect enterprise data solutions | Data Engineering Manager |\n| Data Engineering Manager | 15+ years | Strategy, governance, cross\u2011domain data initiatives | Director of Data Engineering |\n"