Product Owner - Data Engineering (9-16 yrs)

Job Summary & Responsibilities :

Overview :

We are seeking a highly motivated and experienced Product Owner to join our Data Engineering team.

The ideal candidate will have a strong understanding of data engineering principles, excellent communication skills, and the ability to work collaboratively with cross-functional teams.

This role requires a basic understanding of AWS, SQL, Qlik, Data Warehousing, and other relevant information to drive the success of our data initiatives.

Responsibilities :

Product Vision and Strategy :

- Develop and communicate the product vision and strategy for the Data Engineering team, ensuring alignment with the company's overall goals and objectives.

Backlog Management :

- Prioritize and manage the product backlog, ensuring that the most valuable features and improvements are delivered to meet business needs.

Stakeholder Engagement :

- Collaborate with stakeholders, including business leaders, data scientists, and engineers, to gather requirements, define user stories, and ensure the successful delivery of data solutions.

Sprint Planning :

- Lead sprint planning sessions, working closely with the Data Engineering team to define sprint goals and ensure that the team has a clear understanding of the tasks and deliverables.

Release Management :

- Coordinate the release of new features and enhancements, ensuring that they are delivered on time and meet quality standards.

Performance Monitoring :

- Monitor the performance of data solutions, identifying and addressing any issues or areas for improvement to ensure optimal performance and reliability.

Documentation :

- Maintain comprehensive documentation of product features, user stories, and technical specifications to ensure that the team and stakeholders have a clear understanding of the product.

Continuous Improvement :

- Foster a culture of continuous improvement within the Data Engineering team, encouraging the adoption of best practices and the exploration of new technologies and methodologies.

Risk Management :

- Identify and mitigate risks associated with product development and delivery, ensuring that potential issues are addressed proactively.

Training and Support :

- Provide training and support to team members and stakeholders to ensure they have the knowledge and skills needed to use and benefit from the product.

Requirements :

Education :

- Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.

- A master's degree is a plus.

Experience :

- Minimum of 3-5 years of experience as a Product Owner, Business Analyst, or similar role, preferably within a data engineering or data science environment.

Technical Skills :

- With 7-10 yrs experience Basic understanding of AWS, SQL, Qlik, Data Warehousing, and other relevant technologies.

- Experience with data modeling, ETL processes, and data visualization tools is highly desirable.

Agile Methodologies :

Strong knowledge of Agile methodologies, including Scrum and Kanban, with experience leading Agile teams and managing product backlogs.

Analytical Skills :

- Excellent analytical and problem-solving skills, with the ability to understand complex data requirements and translate them into actionable user stories and product features.

Communication Skills :

- Strong verbal and written communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical stakeholders.

Leadership :

- Proven leadership skills, with the ability to inspire and motivate cross-functional teams to

achieve common goals and deliver high-quality data solutions.

Adaptability :

- Ability to thrive in a fast-paced, dynamic environment, with a strong sense of urgency and the ability to manage multiple priorities and deadlines.

Preferred Qualifications :

- Experience with additional data engineering tools and technologies, such as Hadoop, Spark, Kafka, and Python.

- Certifications in AWS, SQL, or other relevant technologies.

- Experience working in a cloud-native environment and leveraging cloud services for data

engineering solutions.

- Familiarity with data governance and data quality frameworks.

- Experience with machine learning and AI-driven data solutions.