Data Engineer

Found in: Talent IN C2 - 2 weeks ago

Bengaluru, India The Nielsen Company Full time
At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future. Nielsen measures the media-consumption habits of homes globally. Our data paints a rich portrait of the audience in those markets we measure. As a pioneer and industry leader in audience measurement for more than half a century, we take pride in our technology and processes, and we are constantly searching for new ways to advance our culture of innovation and growth. The ideal candidate will have a solid background in the Computer Science, Data Science and Analytics or related fields. Additionally, the candidate demonstrates a history of experience working within the Software Development Life Cycle, and exhibits excellent critical thinking, problem-solving, and interpersonal skills. 

Role Details

Analytics team specific: This role drives the acceleration of data acquisition, ensures the reliability and accuracy of data outputs and enhances the accessibility and discovery of data. They offer technical guidance and mentorship, uphold data integrity and reusability, and collaborate with diverse teams to meet our extensive data needs. Meters team specific: In this role, you will learn and become an expert in Nielsen’s systems and TV panel data, with a focus on underlying meter hardware and infrastructure used for data collection and crediting. You will develop and test software and related database infrastructure used to support both research and production pipelines, all while working within the Software Development Life Cycle framework and applying software development best practices.

Responsibilities

Design and automate essential data pipelines and inputs, ensuring seamless integration with downstream analytics and production systems.  Collaborate with cross-functional teams to integrate new functionalities into existing data pipelines, including lower test environments to help validate and assess impact prior to Production integration, where applicable.  Implement data governance and quality processes to ensure the integrity and accuracy of data throughout its lifecycle. Monitor data systems and processes to identify issues and proactively implement improvements to prevent future problems. Participate in code reviews with senior developers prior to pushing the code into production to ensure meeting accuracy and best practice standards. Implement data pipeline Directed Acyclic Graphs (DAGs) and maintenance DAGs. Configure and setup DAGs based on the data to run Spark commands in parallel and sequential.  Perform unit testing using test cases and fix any bugs.  Optimize code to meet product SLAs Support multiple projects and communicate with stakeholders in various organizations. This includes regularly providing status updates, developing timelines, providing insights, etc.

Key Skills

Bachelor’s Degree in Computer Science, Data Science, Analytics or related field  3+ years of experience with the following: Coding in Python, PySpark, and SQL Hive data storage technologies Working within cloud-based infrastructures and tools such as AWS, EC2, GitLab, and Airflow.  Working within the Software Development Life Cycle framework and applying software development best practices Building monitoring checks and tools to ensure infrastructure and related processes are working as expected Solid understanding of system design, data structures and performance optimization techniques Excellent problem solving skills and attention to detail Well-organized and able to handle and prioritize multiple assignments Able to communicate effectively both orally and in writing (Preferred) 2+ years experience with visualization and reporting tools, Tableau (Preferred) Experience deploying and maintaining Machine Learning models within Production environments (Preferred) Experience working with Jira, Confluence, and Smartsheets (Preferred) Experience with Alteryx, Databricks platforms

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