Cloud Data Engineer

Job Description:

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and cloud platforms (AWS/Azure).
• Implement data transformation logic, validation rules, and data quality checks to ensure accuracy, consistency, and reliability of datasets.
• Develop and manage data models, schemas, and data warehouse structures to enable seamless data consumption for analytics and reporting.
• Monitor, troubleshoot, and continuously optimize data pipelines for performance, scalability, reliability, and cost efficiency in cloud environments.
• Ensure adherence to data governance, security, and compliance standards across all data processing and storage layers.
• Collaborate closely with cross-functional teams to deliver scalable, high-quality, and business-aligned data solutions.

Qualification & Experience

• Minimum 2-4 years of experience in a Data Engineering role with a B.Tech/BE or equivalent technical background.
• Strong programming skills in Python and SQL with experience in building and optimizing data pipelines.
• Hands-on experience building ETL/ELT pipelines and cloud data services (Azure or AWS).
• Experience working with Databricks or similar distributed data processing frameworks (e.g., AWS Glue).
• Familiarity with workflow orchestration tools like Airflow and version control systems such as Git.
• Experience handling large datasets, implementing data quality checks, and understanding data ingestion, storage, and consumption architectures.
• Good understanding of data quality, monitoring, and basic DevOps/DataOps practices, along with strong problem-solving and communication skills.