About the Opportunity
This is a full-time opportunity with a leading product-based technology company building large-scale data and digital platforms for global enterprises. The organization works at the intersection of data, cloud, AI, and modern engineering, developing highly scalable platforms that process massive datasets and enable data-driven customer experiences.

Role Overview
We are looking for an experienced Staff Engineer – Data Engineering with strong hands-on expertise in Databricks, Python, PySpark, Apache Spark, and AWS.
This is a senior Individual Contributor (IC) role combining hands-on engineering with architecture and technical leadership. You will design and build large-scale distributed data platforms while influencing engineering standards, platform architecture, scalability, and technical direction.

Key Responsibilities
• Architect, design, and develop large-scale cloud-native data platforms using Databricks, Spark, PySpark, Python, and AWS.
• Build high-performance distributed data processing solutions for massive-scale datasets.
• Design modern Data Lake, Delta Lake, and Data Warehouse architectures.
• Develop batch, real-time, and near-real-time data processing solutions.
• Drive improvements across performance, scalability, reliability, security, governance, and cost optimization.
• Contribute hands-on across solution design, development, deployment, observability, and production readiness.
• Review architectural decisions and establish engineering standards and best practices.
• Collaborate with global Product, Engineering, Architecture, and business teams.
• Mentor engineers and provide technical guidance across complex engineering initiatives.

Required Skills
• 10–14 years of software/data engineering experience with strong hands-on technical expertise.
• Deep expertise in Databricks, Python, PySpark, and Apache Spark.
• Strong experience with Data Lakes, Delta Lake, Data Warehousing, and distributed data processing.
• Hands-on experience with AWS, including services such as S3, Glue, Redshift, EMR, Athena, Lambda, or EventBridge.
• Experience with streaming and messaging technologies such as Kafka, Kinesis, SQS, or RabbitMQ.
• Strong knowledge of SQL and relational/NoSQL databases.
• Experience with Terraform/Ansible, CI/CD, and modern DevOps practices.
• Strong system design, architecture, performance optimization, and problem-solving capabilities.
• Proven ability to influence technical direction while remaining hands-on as an Individual Contributor.