Experience: 8-10+ years, Databricks, Spark, SQL, Python
Job Description & Details
"Data engineering is the backbone of modern analytics, enabling organizations to turn raw data into actionable insights. As businesses migrate to cloud\u2011native platforms like Databricks, the demand for leaders who can architect scalable pipelines has surged. Mastering this niche not only drives career growth but also positions you at the forefront of data innovation.\n\n# Job Summary\nWe are seeking a seasoned Lead Data Engineer to spearhead a Databricks migration, design end\u2011to\u2011end ETL/ELT pipelines, and define the data architecture for a fast\u2011growing analytics team. The role combines hands\u2011on development (Spark, SQL, Python, Azure Data Factory) with strategic leadership over BI tools such as Tableau and ThoughtSpot, while collaborating with global stakeholders.\n\n# Top 3 Critical Skills Table\n| Skill | Why it's critical | Mastery Level |\n|---|---|---|\n| Databricks Migration | Core platform shift to unified analytics, reducing latency and cost | Expert |\n| Apache Spark & Python | High\u2011performance distributed processing and custom transformations | Advanced |\n| Data Architecture & Modeling | Guarantees scalable, reliable data products and future\u2011proof design | Expert |\n\n# Interview Preparation\n1. **Describe the end\u2011to\u2011end steps you would take to migrate an on\u2011premises data warehouse to Databricks.** *Interviewer looks for understanding of data ingestion, Delta Lake, schema evolution, security, and rollback strategy.*\n2. **How do you optimize Spark jobs for both cost and performance?** *Expect discussion on partitioning, caching, predicate push\u2011down, and cluster sizing.*\n3. **Explain the differences between ETL and ELT and when you would choose each in a cloud environment.** *Focus on storage vs compute separation, data lake usage, and latency considerations.*\n4. **What patterns do you use to design a robust data model for BI tools like Tableau?** *Look for dimensional modeling, star/snowflake schemas, and handling slowly changing dimensions.*\n5. **Walk through a real scenario where you implemented data governance (access control, lineage) on Azure Data Factory and Databricks.** *Assess knowledge of Azure RBAC, Unity Catalog, and audit logging.*\n\n# Resume Optimization\n- Led a cross\u2011functional team of 8 engineers to complete a 12\u2011month Databricks migration, cutting query latency by 45%.\n- Designed and deployed over 150 scalable Spark pipelines processing >10\u202fTB daily using Python and SQL.\n- Architected a Delta Lake\u2011based data lakehouse, enabling unified analytics and reducing storage costs by 30%.\n- Implemented CI/CD for data pipelines with Azure DevOps, achieving zero\u2011downtime deployments.\n- Built enterprise\u2011wide data models (star schema) supporting Tableau and ThoughtSpot dashboards for 200+ users.\n- Established data governance framework leveraging Azure RBAC and Unity Catalog, ensuring compliance with GDPR.\n- Optimized Spark jobs via adaptive query execution and dynamic partitioning, saving $200K in compute spend annually.\n- Mentored junior engineers on best practices in PySpark, ADF, and data modeling, improving team velocity by 20%.\n- Conducted performance tuning workshops that reduced average job runtime from 45\u202fmin to 18\u202fmin.\n- Collaborated with global product owners to translate business requirements into technical specifications, achieving 98% stakeholder satisfaction.\n\n# Application Strategy\n1. **Subject Line:** \"Lead Data Engineer \u2013 Databricks Migration Expert \u2013 [Your Name]\"\n2. **Opening Paragraph:** Briefly state your excitement for the role, mention the company (or \u201cyour team\u201d), and highlight 2\u20113 years\u2011relevant achievements.\n3. **Middle Paragraph:** Align your experience with the three critical skills (Databricks, Spark, data architecture). Use quantifiable results.\n4. **Closing Paragraph:** Express eagerness to discuss how you can accelerate their migration, and include a polite call\u2011to\u2011action.\n5. **Signature:** Full name, phone, LinkedIn URL, and attach a tailored resume.\n\n# Career Roadmap\n| Current Role | Typical Experience | Core Focus | Next Position |\n|---|---|---|---|\n| Data Engineer | 3\u20115 years | Pipeline development, SQL, basic Spark | Senior Data Engineer |\n| Senior Data Engineer | 5\u20117 years | End\u2011to\u2011end solutions, cloud platforms, mentoring | Lead Data Engineer |\n| Lead Data Engineer | 8\u201110+ years | Architecture, migration projects, team leadership | Data Engineering Manager / Architect |\n"