We are seeking an experienced Data Engineer with strong expertise in Data Lake, Databricks, and dbt (Data Build Tool) for designing, building, and optimizing modern cloud-based data platforms. The ideal candidate will have hands-on experience in data ingestion, transformation, modeling, orchestration, and analytics enablement across large-scale enterprise environments.
Key Responsibilities
- Design and develop scalable Data Lake solutions on cloud platforms.
- Build and maintain data pipelines using Databricks and Spark technologies.
- Develop, test, and deploy data transformation models using dbt.
- Implement ELT/ETL frameworks for batch and real-time data processing.
- Design and maintain dimensional data models, data marts, and curated data layers.
- Optimize data workflows for performance, scalability, and reliability.
- Collaborate with business stakeholders, data architects, and analytics teams to deliver data solutions.
- Implement data quality checks, monitoring, and governance controls.
- Support CI/CD, release management, and automated deployment processes.
- Troubleshoot and resolve issues related to data pipelines and platform performance.
Mandatory Skills
- 7+ years of experience in Data Engineering.
- Strong hands-on experience with Databricks and Apache Spark (PySpark/Scala Spark).
- Experience in building and managing Data Lake architectures.
- Expertise in dbt (Data Build Tool) for data transformation and modeling.
- Strong SQL programming and performance tuning skills.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Knowledge of data warehousing concepts and dimensional modeling.
- Experience with data orchestration tools and scheduling frameworks.
- Understanding of Git, CI/CD, and DevOps practices.