Location: Jersey City, NJ OR Charlotte, NC (onsite day 1)
Job Type: Contract
Salary: Competitive
Duration: 12+ Months
Experience: 12+ years, Azure Databricks, Python, Scala, SQL
Job Description & Details
"Data engineering on Azure is exploding as companies migrate their analytics to the cloud, making skilled engineers more valuable than ever. This Azure Data Engineer role sits at the heart of that transformation, offering hands\u2011on work with Databricks, Spark, and modern data lakes. With a 12\u2011month contract and on\u2011site presence, it\u2019s a fast\u2011track opportunity to showcase leadership and technical depth.\n\n# Job Summary\nWe are seeking an experienced Azure Data Engineer to design, build, and optimize end\u2011to\u2011end data pipelines on Azure Databricks, Azure Data Lake Storage, and Azure SQL Database. The ideal candidate will write production\u2011grade code in Python, Scala, or SQL, implement robust ETL/ELT processes, and lead a technical team to deliver multiple concurrent projects.\n\n# Top 3 Critical Skills Table\n| Skill | Why it's critical | Mastery Level |\n|---|---|---|\n| Azure Databricks & Spark | Enables scalable data processing & lakehouse architecture | Senior |\n| Data Modeling & ETL | Foundation for reliable pipelines and enterprise data warehousing | Senior |\n| Technical Leadership | Drives project delivery, aligns teams, and ensures quality across initiatives | Senior |\n\n# Interview Preparation\n1. **Describe how you would architect a data lake using Azure Databricks and Azure Data Lake Storage.**\n *What the interviewer is looking for:* Understanding of lakehouse concepts, partitioning strategies, and security controls.\n2. **Explain the differences between ETL and ELT in a Spark environment and when you would choose each.**\n *What the interviewer is looking for:* Knowledge of processing overhead, data movement costs, and performance tuning.\n3. **Walk through a complex Spark job you optimized for performance. Which metrics did you monitor and what changes did you apply?**\n *What the interviewer is looking for:* Hands\u2011on experience with Spark tuning\u2014shuffle partitions, caching, predicate push\u2011down, etc.\n4. **How do you ensure data quality and consistency across multiple pipelines feeding Azure SQL Database?**\n *What the interviewer is looking for:* Approaches to testing, schema enforcement, idempotency, and monitoring.\n5. **Tell us about a time you led a technical team through competing project deadlines. How did you prioritize and communicate?**\n *What the interviewer is looking for:* Leadership style, stakeholder management, and ability to keep projects on track.\n\n# Resume Optimization\n- Azure Databricks\n- Spark\n- Python\n- Scala\n- SQL\n- Azure Data Lake Storage\n- Azure SQL Database\n- Data Modeling\n- ETL/ELT Processes\n- Technical Leadership\n\n# Application Strategy\nWhen reaching out to the recruiter, send a concise email that starts with a friendly greeting, attach your updated resume, and clearly reference the Azure Data Engineer opening. Highlight your top skills\u2014such as Azure Databricks, Spark performance tuning, and team leadership\u2014and cite specific projects where you built end\u2011to\u2011end pipelines on Azure. Make sure to map your experience directly to the key requirements listed in the job description.\n\n# Career Roadmap\n| Current Role | Typical Experience | Core Focus | Next Position |\n|---|---|---|---|\n| Azure Data Engineer | 3\u20115 yrs data engineering, Azure services | Build pipelines, lakehouse implementation | Senior Azure Data Engineer |\n| Senior Azure Data Engineer | 5\u20118 yrs, lead projects | Architecture, performance optimization | Data Architecture Lead |\n| Data Architecture Lead | 8\u201112 yrs, cross\u2011team strategy | Enterprise data strategy, governance | Data Engineering Manager |\n| Data Engineering Manager | 12+ yrs, people & portfolio management | Team growth, stakeholder alignment | Director of Data Engineering |\n"