Highlights
Design scalable solutions, collaborate across teams, provide actionable insights.
Description
Job Summary
pWe are seeking a Media Data Analyst to join our Roundel team. As a key member, you will design and maintain scalable data pipelines, collaborate with cross-functional teams, and provide actionable insights for our media strategies.
Responsibilities
- Design and develop scalable data pipelines aligned with analytics needs.
- Analyze data trends to identify opportunities for improved quality and efficiency.
- Serve as the primary technical resource for Roundel-related data needs.
- Monitor performance and escalate issues transparently for timely resolution.
Required Skills
- Data Engineering
- Analytics
- BI Tools (Power BI, Domo)
- Data Governance Principles
- Stakeholder Management
Required Skills Explained
- Data Engineering: Proficiency in designing and developing scalable data pipelines using tools like Apache Airflow, Apache Kafka, or similar.
- Analytics: Experience with advanced analytics techniques such as statistical analysis and predictive modeling to derive actionable insights from raw data.
- Business Intelligence Tools: Strong working knowledge of BI platforms including Power BI, Domo, and Looker for creating visualization-ready datasets.
- Data Governance: Understanding of principles related to data quality, governance, and ensuring compliance with internal policies and regulations.
- Technical Communication: Ability to translate complex technical concepts into understandable language for non-technical stakeholders.
Who is this for
pThis role is ideal for individuals with a strong technical background in data engineering and analytics. You should have excellent communication skills and the ability to work effectively in a fast-paced environment.
Why This Job is a Good Opportunity
ulliCareer Growth: A role that offers opportunities to work on cutting-edge data solutions, enhancing your skill set in data engineering and analytics.liImpactful Work: Engage with cross-functional teams and contribute to impactful projects that directly influence business outcomes.liWork Environment: Join a dynamic and innovative team within a leading retailer, offering a supportive and collaborative workplace culture.liIndustry Recognition: Be part of an iconic brand known for its guest-centric approach and data-driven marketing strategies.
Interview Preparation Tips
- Understand Data Pipelines: Review examples of ETL processes and familiarize yourself with tools like Apache Kafka or Airflow.
- BI Tools Mastery: Practice working with Power BI, Domo, or Looker to create visualizations from sample datasets.
- Data Governance Principles: Study principles related to data quality, compliance, and governance to ensure you can contribute effectively to team processes.
- Cross-Functional Collaboration: Prepare scenarios where you have collaborated across different teams to solve complex problems.
Career Growth in This Role
pThe role of a Media Data Analyst at Target offers extensive opportunities for career growth. You will start by contributing to the design and implementation of scalable data solutions, which can lead to advanced roles such as Senior Data Engineer or Data Science Manager. The hands-on experience with data engineering and analytics will enhance your technical skills, positioning you well for future leadership positions.pAdditionally, your ability to collaborate across teams and understand business requirements will make you a valuable asset, opening doors for roles in project management, product development, and strategic planning. Continuous learning through workshops or certifications can further accelerate your career progression within the company or beyond.
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Skills
Frequently Asked Questions
What kind of data tools will I be working with?You will work with BI tools like Power BI, Domo, and Looker to design and maintain data pipelines.
Is this role suitable for someone new to the field?We are looking for candidates with proven experience in data engineering and analytics. Prior experience is preferred but not required.
What are the expectations regarding collaboration?You will need to collaborate closely with Engineering, Data Science, and Product teams to enhance data availability and meet business demands.
