Description

Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes
• Build and manage data architectures using cloud platforms (preferably Azure)
• Develop APIs and backend services to serve data applications
• Create interactive dashboards and data visualization solutions
• Collaborate with cross-functional teams to understand data requirements and deliver solutions
• Ensure data quality, integrity, and security across systems
• Optimize data workflows for performance and scalability
• Work with structured and unstructured data from multiple sources
• Implement data warehousing solutions and data lake architectures
• Leverage AI-assisted development tools and modern engineering practices to accelerate delivery
• Continuously explore new technologies and improve data engineering processes

Skills and Qualifications:

• Strong proficiency in Python, SQL, and at least one programming language (Java/Scala preferred)
• Experience with data processing frameworks such as Apache Spark, Hadoop, or similar
• Hands-on experience with Azure Data Services (Azure Data Factory, Azure Synapse, Data Lake, etc.)
• Experience building RESTful APIs and working with microservices architecture
• Knowledge of data modeling, ETL/ELT processes, and data warehousing concepts
• Familiarity with BI tools such as Power BI, Tableau, or similar
• Understanding of distributed systems and big data technologies
• Experience with version control tools like Git
• Strong problem-solving and troubleshooting skills

Education and Experience:

• Bachelor’s degree in computer science, Engineering, or a related field (or equivalent work experience)
• 5 to 8 years of experience in data engineering and full stack development

Preferred Qualifications:

• Experience with real-time data processing (Kafka, Spark Streaming, etc.)
• Familiarity with Agile methodologies
• Experience with CI/CD pipelines and DevOps practices
• Knowledge of data governance, security, and compliance standards
• Experience with containerization tools like Docker and Kubernetes
• Exposure to machine learning workflows and data science collaboration

Key Skills

Education

Bachelor's degree