Manager, Data Operations

About the role

Meredith Operations Corporation has an opening for a Manager, Data Operations in New York, NY. The position duties are as follows:

Responsibilities

• Responsible for leading and scaling the Data Operations team.
• Collaborate across business, analytics, and data science teams to design, build, and maintain robust data pipelines that power reporting, analytics, and business insights.
• Daily duties include:
  • Design, implement, and optimize performant, well-documented data models that enable self-service analytics and strategic initiatives (10%)
  • Collaborate with stakeholders to understand business needs, gather requirements, and deliver high-quality data solutions that support reporting and decision-making (30%)
  • Conduct ad-hoc data analyses to address ongoing business and customer questions, and translate emerging insights into recommendations for the data and technology roadmap (20%)
  • Define and champion engineering best practices around code quality, documentation, version control, and testing within analytics workflows (10%)
  • Stay up to date on industry trends and new technologies to continuously improve our data architecture, tooling, and processes (10%)
  • Manage and mentor a team of data engineers responsible for building and maintaining core data models, dashboards, and scalable data products (20%)
• Hybrid position, permits telecommuting - Must live within normal commuting distance of New York, NY office to facilitate office visits 2 times per week.
• The position requires at minimum a Bachelor’s degree in Computer Science, Statistics, Data Science, Information Systems Engineering, a related field or foreign equivalent, plus 7 years of experience in any occupation where data analytics experience was gained. Alternatively, employer will accept a Master’s degree in Computer Science, Statistics, Data Science, Information Systems Engineering, a related field or foreign equivalent, and 5 years of experience in any occupation where data analytics experience was gained.

Requirements

• Experience must include: 5 years of experience building and optimizing data pipelines using Python (must include experience with data scripting, automation, and building data tooling).
• 5 years of advanced SQL experience working with relational and distributed data systems (e.g., Hive, BigQuery).
• Must include 5 years of experience developing complex queries with multiple datasets, and optimizing queries for best performance.
• 5 years of experience with data visualization, including Looker or Looker Studio.
• 5 years of experience with cloud data platforms to include at least BigQuery or GCP.
• 5 years of experience working in a Linux/Unix environment.
• 3 years of experience with dbt for data transformation and pipeline management, to include design for complex data modeling for large scale data sources.
• 3 years of experience with core data engineering concepts, including data pipelines and ETL/ELT processes.
• 2 years of experience leading or mentoring a team of data or analytics engineers, or owning end-to-end delivery of large-scale (with TB data processing) data products.
• 2 years of experience managing and influencing stakeholder requests, expectations, and relationships across a variety of complex business domains at a strategic level.
• 2 years of experience translating complex technical concepts into clear business insights for diverse audiences, working cross-functionally with analysts, product managers, and executives.
• Demonstrated understanding of data governance, data quality, and data security best practices.

Qualifications

• Minimum required education: Bachelor’s degree in Computer Science, Statistics, Data Science, Information Systems Engineering, a related field or foreign equivalent.
• Minimum required experience: 7 years of experience in any occupation where data analytics experience was gained. Alternatively, a Master’s degree in Computer Science, Statistics, Data Science, Information Systems Engineering, a related field or foreign equivalent, and 5 years of experience in any occupation where data analytics experience was gained.

Skills

• Python
• Advanced SQL
• Data visualization (Looker or Looker Studio)
• Cloud data platforms (BigQuery or GCP)
• Linux/Unix environment
• dbt for data transformation and pipeline management
• Data engineering concepts (data pipelines, ETL/ELT processes)
• Leading or mentoring a team of data or analytics engineers
• Managing and influencing stakeholder requests
• Translating complex technical concepts into clear business insights
• Data governance, data quality, and data security best practices

Benefits

See details in the "Pay" section.

Pay

New York: $167,835 - $175,000

Schedule

Hybrid position, permits telecommuting - Must live within normal commuting distance of New York, NY office to facilitate office visits 2 times per week.