Technical Product Manager, Data Platforms

New York Times - New York, NY

Full-time - Mid Level

New York, NY

Publishing Industries

About the position

The Technical Product Manager for the Data Platform Mission will play a crucial role in empowering the organization to effectively access and utilize data for strategic decision-making and enhancing user experiences. This position involves collaborating with various teams to develop data products and improve the overall data infrastructure, ensuring that data collection, processing, and usage are efficient and impactful.

Responsibilities

• Partner with data leaders to create a coordinated data products roadmap.
• Deliver user-friendly, high-quality data products that enhance data-driven decision-making.
• Facilitate experiences for data analysts, scientists, and product managers to discover and utilize information effectively.
• Establish data product lifecycle and processes for delivering high-quality data products.
• Collaborate with teams to understand their data and analytics needs and prioritize requests accordingly.
• Work with product and engineering teams to communicate progress and deliver impactful solutions.
• Deliver iterative products that provide incremental value and gather quick feedback from stakeholders.
• Utilize qualitative and quantitative methods to measure the impact of data products.

Requirements

• 2+ years of experience designing and building data products as a product manager or in a similar role.
• Proven track record of implementing complex data systems with supporting data analysis and optimization.
• Experience with data handling approaches and technologies.
• Understanding of data governance, data modeling, data pipelines, and data infrastructure.
• Ability to communicate complex technical concepts to diverse audiences.

Nice-to-haves

• Background in software development, engineering, data science, or analytics.
• Hands-on experience in developing data products.
• Familiarity with data querying languages and technologies such as SQL, Python, BigQuery, AWS, and Spark.