Manager, Data Operations

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. * Collaborate with stakeholders to understand business needs, gather requirements, and deliver high-quality data solutions that support reporting and decision-making. * Conduct ad-hoc data analyses to address ongoing business and customer questions, and translate emerging insights into recommendations for the data and technology roadmap. * Define and champion engineering best practices around code quality, documentation, version control, and testing within analytics workflows. * Stay up to date on industry trends and new technologies to continuously improve our data architecture, tooling, and processes. * Manage and mentor a team of data engineers responsible for building and maintaining core data models, dashboards, and scalable data products. Role will supervise approx. 2 subordinates with the title of Senior Data Engineer (Database Architects 15-1243.00 occupation code), subject to business needs. Minimum Requirements: Requires a Bachelors 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 Masters 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. Experience must include: 1. 5 years of experience building and optimizing data pipelines using Python (must include experience with data scripting, automation, and building data tooling). 2. 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. 3. 5 years of experience with data visualization, including Looker or Looker Studio. 4. 5 years of experience with cloud data platforms to include at least BigQuery or GCP. 5. 5 years of experience working in a Linux/Unix environment. 6. 3 years of experience with dbt for data transformation and pipeline management, to include design for complex data modeling for large scale data sources. 7. 3 years of experience with core data engineering concepts, including data pipelines and ETL/ELT processes. 8. 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. 9. 2 years of experience managing and influencing stakeholder requests, expectations, and relationships across a variety of complex business domains at a strategic level. 10. 2 years of experience translating complex technical concepts into clear business insights for diverse audiences, working cross-functionally with analysts, product managers, and executives. 11. Demonstrated understanding of data governance, data quality, and data security best practices. Hybrid position, permits telecommuting - Must live within normal commuting distance of New York, NY office to facilitate office visits 2 times per week. Offered Wage Range: $167,835 - $175,000/year. CV to [email protected], Ref. MOC-SN1