Analytics & Data Engineering

About the Role

In this Analytics & Data Engineering role at Cognizant Softvision, you will be responsible for designing, developing, and maintaining large-scale data systems and architectures. Your primary focus will be on leveraging various data tools and technologies to extract insights from complex data sets and drive business growth.

As a key member of the data engineering team, you will collaborate with cross-functional teams to identify business requirements, design data pipelines, and implement data warehousing solutions. Your expertise in data engineering will enable you to develop scalable and efficient data processing systems that meet the needs of the organization.

Key Responsibilities

• Design and develop large-scale data systems and architectures using various data tools and technologies.
• Collaborate with cross-functional teams to identify business requirements and design data pipelines.
• Implement data warehousing solutions using Azure Data Factory, Databricks, and Snowflake.
• Develop and maintain scalable and efficient data processing systems using Pyspark and SQL.
• Work with data scientists to develop and deploy machine learning models using MLOPS Engineer.
• Ensure data quality, security, and governance by implementing data validation, data encryption, and access controls.
• Stay up-to-date with emerging trends and technologies in data engineering and apply them to improve data processing systems.

Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
• Strong understanding of data engineering concepts, data warehousing, and data processing systems.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with data tools and technologies such as Azure Data Factory, Databricks, Snowflake, Pyspark, and SQL.
• Knowledge of machine learning concepts and experience with MLOPS Engineer.
• Experience with data validation, data encryption, and access controls.
• Strong problem-solving skills and ability to work in a fast-paced environment.

What You'll Learn

In this role, you will have the opportunity to learn and grow in the field of data engineering. You will gain hands-on experience with various data tools and technologies, and develop a strong understanding of data warehousing and data processing systems. You will also have the chance to work with cross-functional teams and collaborate with data scientists to develop and deploy machine learning models.

As you progress in your career, you will be able to apply your skills and knowledge to drive business growth and improve data processing systems. You will also have the opportunity to stay up-to-date with emerging trends and technologies in data engineering and apply them to improve data processing systems.

Resume Tip

When applying for this role, make sure to highlight your experience with data tools and technologies, such as Azure Data Factory, Databricks, Snowflake, Pyspark, and SQL. Also, be sure to emphasize your knowledge of machine learning concepts and experience with MLOPS Engineer. Additionally, highlight your problem-solving skills and ability to work in a fast-paced environment.

Use specific examples from your previous experience to demonstrate your skills and knowledge. For example, you could describe a project where you designed and developed a large-scale data system using Pyspark and SQL, or a project where you implemented a data warehousing solution using Azure Data Factory and Databricks.