Who we are
Twitter is looking for exceptionally talented and open-minded engineers to join the Customers Analytics team to build the Data Engineering function.
Our team is the foundation for driving data-informed decision-making across the Customers (Ad Revenue) Org. We partner closely with engineering, data science, and operations teams to build the platform for insights that drive growth, efficiency, and innovation.
What you’ll do
In this role, you’ll be the key to unlocking large-scale, complex datasets. Your work will directly impact decision-making for our partner teams, translating into actionable insights and driving bottom-line growth.
Working closely with product teams to build mission-critical data pipelines and products that are ‘source of truth’, as well as state-of-the-art data warehouse solutions, you will collaborate closely with data scientists, analysts, engineers, product managers, and many other data consumers across the company.
Key Responsibilities:
Closely collaborate with technical and non-technical partner teams to understand data needs, draft technical requirements and advise on solutions
Design and own the architecture for large scale projects that involve Twitter-wide data
Outline, develop, and launch extremely efficient and reliable data pipelines tailor-made to address the needs of the Customers org
Define and manage SLA for all data sets
Manage security and privacy requirements, address data quality issues, and drive a rigorous governance process
Foster cross-functional knowledge sharing to identify data opportunities and drive impact
Who you are
You are keen to understand the business and translate data needs into technical requirements.
You can effectively communicate with different functionalities (engineering, data science, operations teams, and non-technical functions) to craft a roadmap and measures of success
You possess the ability to thrive in an unstructured environment, working autonomously on a strong team to find opportunities and deliver business impact
You are passionate about learning or growing your expertise in some or all of the following:
Data Pipelines
Data Warehousing
Statistics
Metrics Development