IT Data Engineer Job in Bengaluru at Tyson Foods

TYSON Food is hiring for the role for IT Data Engineer!

Responsibilities of the Candidate:

• Design, implement, and optimize data pipelines with a strong focus on SQL and scripting.
• Develop and maintain ETL processes and contribute to data warehousing solutions, including understanding star schema and Kimball or Snowflake methodologies.
• Write and optimize SQL and calculations within data visualization tools to enhance data models and performance.
• Enforce data governance policies and ensure compliance with data security standards.
• Build, deploy, and support data visualization solutions that effectively communicate data insights.
• Collaborate with stakeholders to understand their requirements and deliver intuitive, visually appealing dashboards.
• Participate in cloud cost optimization efforts, ensuring efficient use of cloud resources.
• Contribute to the development of data architecture and support data streaming initiatives.
• Implement basic data pipeline orchestration and assist in integrating big data technologies.
• Communicate and collaborate with key internal stakeholders to align data solutions with business needs.
• Perform other assigned job-related duties that align with our organization's vision, mission, and values and fall within your scope of practice.

Requirements:

• 1+ years relevant or practical experience.
• Proficiency in SQL and basic ETL tools.
• Understanding of data warehousing concepts and basic data architecture.
• Familiarity with data pipeline orchestration and monitoring.
• Initial exposure to big data technologies like Hadoop or Apache Spark.
• Initiative: Proactively identifying and proposing data solutions.
• Teamwork: Collaborating effectively with stakeholders across departments.
• Communication: Ability to explain complex data concepts to non-technical audiences.
• Critical Thinking: Analyzing data architecture needs and proposing improvements.
• Adaptability: Quickly learning and applying new big data technologies.
• Time Management: Balancing multiple projects and priorities effectively.
• Attention to Detail: Ensuring data accuracy and quality in all processes.