At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.
As a Sr. Data Engineer, Analytics at Gracenote, you will be instrumental in deriving insights from our vast Entertainment datasets and production systems. This role entails a blend of technical prowess and business acumen, requiring strong expertise in SQL, Python, and proficiency with AWS cloud services. The successful candidate will not only be adept at analyzing data but also skilled in communicating these insights through reports and dynamic dashboards that support both technical and non-technical audiences.
Responsibilities
- Create and maintain production dashboards to monitor key performance indicators and drive business decisions.
- Aggregate, clean and study data for key or specialized analytics projects.
- Utilize Python for complex data manipulation, analysis, and automation tasks.
- Work closely with business units to gather requirements and translate business needs into technical specifications.
- Offer data-driven recommendations to leadership, influencing strategic planning and operations.
Qualifications
- Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
- Proficient in AWS cloud services fundamentals.
- Proficient in SQL and Python for advanced data analysis.
- Strong skills in data visualization and reporting.
- Exceptional analytical, problem-solving, and communication abilities.
- Capable of working both independently and as part of a collaborative team.
Bonus Skills:
- Experience with Apache Spark/PySpark
- Experience training/evaluating machine learning models
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