Key Responsibilities :

- Design, build, and optimize scalable, reliable, and efficient ETL/ELT pipelines for processing large datasets.

- Automate data workflows to ensure real-time and batch data availability.

- Develop and manage data solutions using Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure SQL.

- Work with AWS services such as AWS Glue, Amazon Redshift, Amazon S3, AWS Lambda, and Amazon Athena to build robust data solutions.

- Integrate structured, semi-structured, and unstructured data from multiple sources.

- Create and maintain data models to support analytics and reporting requirements.

- Work closely with Data Scientists, Data Analysts, Software Engineers, and other cross-functional teams.

- Translate business requirements into technical specifications and scalable data solutions.

- Manage IAM roles, policies, and encryption for data at rest and in transit.

- Mentor and guide junior data engineers within the team.

- Apply AI/ML and Generative AI capabilities to data engineering use cases where applicable.

- Monitor and optimize the performance of cloud data pipelines and infrastructure.

- Debug and resolve data-related issues in a timely manner.

Required Qualifications :

- Bachelor's degree in Computer Science, Engineering, or a related field.

- 6 - 11 years of hands-on experience in cloud data engineering, with strong exposure to Azure and AWS.

- Strong experience with Azure Databricks and AI/ML workloads.

- Proficiency in Python, SQL, and scripting languages for data manipulation and automation.

- Experience with data orchestration tools such as Apache Airflow and relevant cloud services.

- Strong understanding of distributed computing and big data frameworks, including Apache Spark and Hadoop.

- Knowledge of cloud data warehouses such as Azure Synapse Analytics and Snowflake.

- Experience with CI/CD pipelines for data workflows using Jenkins, GitHub Actions, or Azure DevOps.

- Relevant Azure, AWS, and/or Databricks certifications are preferred.

- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.

- Strong problem-solving skills with the ability to work independently and collaboratively.

Preferred Candidate Profile :

- Strong hands-on experience delivering enterprise-scale cloud data engineering solutions.

- Experience working across both Azure and AWS cloud environments.

- Good understanding of modern data architecture, data governance, security, and cloud best practices.

- Exposure to AI/ML and Generative AI applications within data engineering.

- Strong communication, mentoring, and stakeholder-management skills.