Data Product Owner - US

Overview

Full Time

Skills

SQL
Kafka
Azure
NOSQL
Data Analysis
ETL processes
Understand of table)
and PySpark
Redis)
and cloud services (e.g.
AWS).

Job Details

Role: Data Product Owner

Location: Canada/US(Florida)-Remote

Duration: Fulltime

Job Description:

Must Have: Data Engineer (atleast 4-5 years of experience, Data Analysis, Understand of table), SQL

Experience Level: 8-13 Years

Responsibilities:

  • Strong understanding of data architecture, modeling, and the ability to work closely with data engineers to oversee the development of data solutions.
  • Expertise in identifying business needs and translating them into technical requirements for data processing and analytics.
  • Proficiency in managing complex projects, prioritizing tasks, and meeting deadlines. Experience with agile methodologies and tools like Jira is essential.
  • Familiarity with data governance principles and practices to ensure that the data strategies align with legal and business standards.
  • Ability to communicate effectively with stakeholders including Business Partners, and technical teams to ensure clarity and alignment on objectives.
  • Strong analytical skills to troubleshoot and resolve data-related issues, optimizing data flows and quality.
  • Hands-on experience with SQL, data warehousing solutions, ETL processes, and PySpark
  • Understanding of the industry and how data-driven insights can drive business strategies and decisions.
  • Ability to lead and inspire teams, acting as a liaison between technical and non-technical stakeholders.
  • Knowledge of quality assurance practices to oversee the testing and validation of data solutions.
  • The capacity to adapt to new challenges and changes in the business environment or technology landscape.

Qualifications:

  • Bachelor's degree in a quantitative field such as Computer Science, Data Science, or equivalent work experience; master's degree preferred.
  • Solid foundation in data structures, algorithms, and system design.
  • Experience with modern data storage, messaging, and processing tools (e.g., SQL, NoSQL, Kafka, Redis), and cloud services (e.g., Azure, AWS).
  • Proficiency in one or more programming languages relevant to data engineering, such as Python, Java, or Scala.
  • Strong interpersonal skills with the ability to convey complex data concepts to non-technical stakeholders.
  • Certification in Project Management Professional (PMP), Certified Scrum Master (CSM), or similar credentials is a plus.