We are looking for an experienced Senior Data Engineer with 8+ years of experience in data engineering, data platforms, and analytics. The ideal candidate should have strong hands-on experience with Databricks, Apache Spark, Cloud Platforms, and CI/CD and should be capable of designing, developing, and optimizing scalable enterprise data solutions.
Candidates with a career gap are also welcome to apply, provided they have strong relevant technical experience.
Must-Have Skills
- Databricks
- Apache Spark
- AWS / Azure / Google Cloud Platform (GCP)
- CI/CD – Continuous Integration & Continuous Delivery
- Data Engineering
- Distributed Computing
- Spark Runtime Internals
- MLOps
Key Responsibilities
- Design, develop, and optimize scalable enterprise data solutions using Databricks.
- Build and manage distributed data processing solutions using Apache Spark.
- Develop high-performance and reliable data pipelines for enterprise-scale applications.
- Apply strong knowledge of Spark architecture and runtime internals to optimize workloads.
- Work with AWS, Azure, or GCP, with deep expertise in at least one major cloud platform.
- Implement and manage CI/CD pipelines for production deployments.
- Support MLOps workflows and integrate data engineering solutions with machine learning platforms.
- Utilize advanced Databricks capabilities to improve data processing, performance, and scalability.
- Troubleshoot and optimize data pipelines, workloads, and platform performance.
- Ensure data platforms meet enterprise standards for security, reliability, scalability, and operational efficiency.
- Collaborate with Data Architects, Data Scientists, Analytics Teams, and Business Stakeholders.
- Contribute to enterprise-scale data transformation and consulting engagements.
Pay: ₹100,000.00 - ₹200,000.00 per month
Application Question(s):
Work Location: Remote
