Senior Member Technical Staff - Data Engineer at TheNielsenCompany

Gracenote, a Nielsen company, is dedicated to connecting audiences to the entertainment they love, powering a better media future for all people. Gracenote is the content data business unit of Nielsen that powers innovative entertainment experiences for the world’s leading media companies. Our entertainment metadata and connected IDs deliver advanced content navigation and discovery to connect consumers to the content they love and discover new ones. Gracenote's Data Organization is a dynamic and innovative group that is essential in delivering business outcomes through data, insights, predictive & prescriptive analytics. An extremely motivated team that values creativity, experimentation through continuous learning in an agile and collaborative manner. From designing, developing and maintaining data architecture that satisfies our business goals to managing data governance and region-specific regulations, the data team oversees the whole data lifecycle.    • Oversee Data infrastructure to ensure robust deployment and monitoring of the pipelines and processes. • Stay ahead of emerging trends in Data, cloud, integrating new research into practical applications. • Mentor and grow a team of junior data engineers. Skill Necessities : • Expert-level proficiency in Python, SQL, and big data tools (Spark, Kafka, Airflow). • Bachelor's degree in Computer Science, Engineering, or related field; Master's degree preferred • Expert knowledge of SQL and experience with relational databases (e.g., PostgreSQL, Redshift, TIDB, MySQL, Oracle, Teradata) • Extensive experience with big data technologies (e.g., Hadoop, Spark, Hive, Flink) • Proficiency in at least one programming language such as Python, Java, or Scala • Experience with data modeling, data warehousing, and building ETL pipelines • Strong knowledge of data pipeline and workflow management tools (e.g., Airflow, Luigi, NiFi) • Experience with cloud platforms (AWS, Azure, or GCP) and their data services. AWS Preferred • Hands on Experience with building streaming pipelines with flink, Kafka, Kinesis. Flink Preferred.   • Understanding of data governance and data security principles • Experience with version control systems (e.g., Git) and CI/CD practices