🛠 Tech Stack

💼 About This Role

You'll take ownership of designing scalable data architectures using Databricks and cloud platforms. Your work will power advanced analytics and customer experience insights at enterprise level. This senior role offers the opportunity to shape core data infrastructure for mission-critical analytics.

🎯 What You'll Do

• Design and own scalable data architectures using Databricks and cloud platforms.
• Build and maintain robust ETL/ELT pipelines with PySpark, SQL, and Databricks Workflows.
• Optimize large-scale distributed data systems through performance tuning and partitioning.
• Implement CI/CD pipelines for data workflows using Git-based systems and DevOps tools.

📋 Requirements

• 8+ years of experience in data engineering, with at least 3 years in senior or staff-level role.
• Strong hands-on expertise in Databricks, including Spark, Delta Lake, and cluster optimization.
• Advanced proficiency in Python, SQL, and PySpark for large-scale data processing.
• Experience with cloud platforms such as Azure, AWS, or GCP (Azure preferred).

✨ Nice to Have

• Exposure to streaming technologies such as Kafka or Event Hubs.
• Familiarity with data governance and observability tools (e.g., Great Expectations, Monte Carlo).
• Mentoring experience and collaboration with cross-functional teams.

🎁 Benefits & Perks

• 💰 Competitive compensation aligned with senior engineering roles.
• 🏢 Hybrid work model with initial on-site collaboration followed by flexible remote options.
• 🚀 Enterprise-scale data platforms and advanced analytics systems.
• 📈 Strong career growth in a high-impact senior technical role.
• 🌍 Global collaboration with data, analytics, and product teams.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3System Design Interview· 60 min