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Senior Analytics Engineer

Lead analytics engineering for Reddit's Sales and Marketing teams, building scalable data pipelines, ETLs, dashboards, and self-service tools to empower data-driven decision making. Requires 4-5+ years experience with large-scale ETL systems, Python/SQL, and data modeling; advanced quantitative degree required.

191k – 267kUnited StatesData EngineeringRemote5+ YOE

About the role

Responsibilities

  • Be the Analytics Engineering lead within the Sales and Marketing organization and a key contributor to the success of Data Science data quality, performance, and automation initiatives.
  • Be the data steward for Sales and Marketing: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for business tracking, advertiser outreach and acquisition, marketing campaigns, and other data-driven activities.
  • Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines.
  • Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.
  • Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service.
  • Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners.
  • Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.

Requirements

  • Advanced degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics.
  • For M.S. holders: 5+ years of industry experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.
  • For Ph.D. holders: 4+ years of industry experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.
  • Experience working in Sales and Marketing domains.
  • Strong programming proficiency in Python, SQL, Spark, Scala, etc.
  • Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data.
  • Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering.
  • Experience in data visualization and dashboard design, including tools such as Looker, Tableau, R visualization packages, Streamlit, D3, and other libraries.
  • Deep understanding of technical and functional designs for relational and MPP Databases.
  • Proven track record of cross-functional execution and collaboration. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen.
  • Experience in mentoring junior data scientists and analytics engineers.
  • Self-starter, ability to work independently and autonomously, as well as part of a team.

Nice to Have

  • Sales and Marketing domain experience
  • Past experience collaborating closely with data scientists, sales, and marketing managers

Benefits

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

Skills

PythonSQLSparkScalaAirflowLookerTableauStreamlitD3ETLELTData ModelingData Visualization

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