Staff Data Engineer, Ads
Company
Location
San Francisco, CA
Type
Full Time
Job Description
We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. As a Data Engineering lead on the Ads Data Science team, you will work closely with various cross-functional teams such as product, marketing, sales, engineering, and operations to develop infrastructure and deliver tools or data structures that enable data-driven decision-making.
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Successful candidates will exhibit technical acumen and business savviness with a passion for making an impact by enabling both producers and consumers of data insight to work smarter. You will achieve a Reddit-wide impact by creating a first-class Ads data warehouse and data tools to provide scalable solutions that meet a wide range of evolving needs - including high-quality metric reporting, product insights, and data engineering for ML models. You will play a critical role in making Ads data more accessible across reddit - unlocking innovation through the self-service of our data from Engineering to Sales teams. If you are passionate about building high-quality data products and leading a strategy to create an agile but reliable foundation to accelerate our advertising business, Reddit will be the perfect home for you.
Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.
Responsibilities:
- Act as the analytics engineering lead within Ads DS team and a key contributor to the success of data science data quality and automation initiatives.
- You will have a keen interest in the collection and quality of underlying data (experiment design and analysis, data deep dive) and in working on ETLs, reporting dashboards, and data aggregations needed for business tracking and/or ML model development.
- 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. Driver widespread adoption of these tools and applications
- 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 analysts
- 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
Required Qualifications:
- MS or PhD in a quantitative discipline: engineering, statistics, operations research, computer science, informatics, applied mathematics, economics, etc.
- 7+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable, object-oriented code (Python preferred) in a production environment.
- Strong programming proficiency in Python, SQL, Spark, Scala, etc.
- Experience with data modeling, ETL (Extraction, Transformation & Load) 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, etc.
- 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.
- 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:
- Ads domain experience, including metrics, tracking, and ads product understanding, is a big plus
- Past experience collaborating closely with data scientists, machine learning engineers, and product managers.
Benefits:
- Comprehensive Healthcare Benefits
- 401k Matching
- Workspace benefits for your home office
- Personal & Professional development funds
- Family Planning Support
- Flexible Vacation (please use them!) & Reddit Global Wellness Days
- 4+ months paid Parental Leave
- Paid Volunteer time off
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please contact us at [email protected].
Date Posted
01/23/2025
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