Responsibilities:

• Design, develop, and deploy scalable and reliable data pipelines to ingest, process, and analyze large volumes of structured and unstructured data.
• Collaborate with cross-functional teams to understand data requirements and design efficient models and schemas.3. Implement data processing workflows using technologies like Informatica BDM, Apache Spark, Apache Flink, or similar distributed computing frameworks.
• Optimize and tune data pipelines for performance, reliability, and scalability.
• Ensure data quality and integrity throughout the data pipeline by implementing data validation and monitoring processes.
• Manage and maintain data infrastructure, including data warehouses, data lakes, and ETL tools.
•  Work closely with data scientists and analysts to provide them with clean, reliable, and accessible data for analysis and reporting.
• Stay up-to-date with emerging technologies and trends in data engineering and recommend new tools and techniques to improve efficiency and productivity.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 2-3 years of experience in data engineering or a similar role.
• Proficiency in programming languages such as Python, Java, or Scala.
• Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, etc.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Strong SQL skills and experience with relational and NoSQL databases.
• Solid understanding of data warehousing concepts and best practices.
• Hands on experience in Informatica BDM, SSIS is must 
•  Excellent problem-solving and analytical skills.
•  Strong communication and collaboration skills, with the ability to work effectively in a team environment.

Preferred Qualifications:

• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Familiarity with machine learning frameworks and libraries.
• Experience with data visualization tools like Tableau, Power BI, etc.
• Certifications in relevant technologies (e.g., AWS Certified Big Data - Specialty, Google Professional Data Engineer, etc.).