Data Ops Engineer

Job Responsibilities

• Work with stakeholders to develop end-to-end cloud-based solutions with a focus on applications and data.
• Collaborate with BI/BA analysts, data scientists, data engineers, DevOps cloud engineers, product managers, and other stakeholders across the organization.
• Ensure delivery of reliable software and data pipelines using data engineering best practices, including secure automation, version control, CI/CD, and proper testing.
• Own the product and influence strategy by helping define the next wave of data insights and system architecture.
• Guide teams in designing, building, testing, and deploying changes to existing software.
• Ensure system security while updating code and improving performance.
• Manage simultaneous updates to sections of data engineering code and other program components.
• Use data to discover opportunities for automation.
• Align with the latest data trends and adopt ways to simplify data insights.
• Be an essential part of the analytics and data insights team, contributing to the technological and architectural vision.

Basic Qualifications

• Minimum 3+ years of hands-on experience in data integration, DevOps, engineering, and analytics.
• Degree in Science, Technology, Engineering, or Mathematics (STEM) or a related discipline.
• Proficiency in SQL, Python, and distributed source control systems such as GIT.
• Experience working in an Agile-Scrum environment.
• Strong scripting skills in languages such as Ruby, PHP, Perl, and Python.
• Excellent interpersonal, management, and decision-making skills.
• Experience with ETL pipelines and workflow management tools like Airflow.
• Strong understanding of dimensional modeling and data warehousing methodologies.
• Ability to identify ways to improve data quality and reliability.
• Commitment to teamwork and strong business communication skills.

Preferred Qualifications

• Experience within the retail industry.
• Passion for working with large data sets and deriving insights.
• Familiarity with identifying tasks suitable for automation using data.
• Awareness and alignment with the latest trends in data analytics and cloud-based data solutions.