Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

About Data Science and Engineering organization:

Data Science and Engineering (DSE) is a key pillar of Netflix's data-driven strategy, leveraging data, analytics, experimentation, models, and consumer insights to make informed decisions. DSE focuses on data engineering, metrics, analysis, dashboards, analytic tools, experimentation research, and analytics. It also develops models and algorithms for internal decision support.

We pride ourselves on using data to inform our decision-making as we work towards our mission. This requires curating data across various domains, such as Growth, Finance, Product, Content, and Studio. All of this data collection and curation is made possible thanks to Netflix's amazing Data Engineers, who bring this data to life.

About Data Engineering:

Data Engineering at Netflix is a role that requires building systems to process data efficiently and modelling the data to power analytics. These solutions can range from batch data pipelines that bring business metrics to life to real-time processing services that integrate with our core product features. In addition, we require our Data Engineers to have a rich understanding of large distributed systems on which our data solutions rely. Candidates should have knowledge across several of these skill sets and usually need to be deep in at least one. As a Data Engineer, you also need to have strong communication skills since you will need to collaborate with business, engineering, and data science teams to enable a culture of learning.

We are hiring for the first time for the Data Engineering organisation in EMEA and across the following Data Engineering teams:

Conversation, Marketing & Fandom Data Engineering 

The reach of Netflix and the fandom we create fuels the “Netflix effect” - a virtuous cycle of great content and intense fandom that catapults our stories into the cultural conversation. Netflix influences what people around the world search for and talk about, the music they listen to, the books they read, the countries they visit, and how they dress. 

Our marketing efforts help to kick-start the Netflix effect, and we are providing more and more ways for fans to engage with our stores: Tudum, events like Netflix Bites and Bridgerton experiences, and the launch in 2025 of the first two Netflix House locations. 

We also create and measure the social buzz with performance marketing and acquisition marketing for Netflix, Netflix Games, Ads, and more. 

In this team, you’ll help elevate our conversation, marketing, and fandom decisions and events globally. You will own and architect our data engineering pipelines to ingest marketing and fandom data from various sources and power insights using the data.

Security Data Engineering

This team is responsible for developing data products that deliver critical insights into security, fraud, and technology risks across customer accounts and internal systems. You will play a key role in enabling our security teams to detect and mitigate security risks within our extensive cloud technology infrastructure. Our infrastructure environment is large and complex, with intricate topology, access controls, security policies, and usage patterns. Centralizing diverse data points to enhance our understanding of these dimensions is essential for success in this role.

Member Data Engineering

The Netflix product experience helps our Members discover the next great piece of content to enjoy.  It could be a new series, an old movie, a live event people are talking about, or even a new video game.  The Product has to put the right content, in the right format, in front of the right people, at the right time.  When we do that well, Members value Netflix and continue to subscribe, despite the many other choices for entertainment.  This team creates the data products that help measure this experience, track key KPIS, and support innovation decisions through A/B testing.  You will partner closely with Engineering teams to refine the client and server logging that serves as a foundation for our analytic datasets and work closely with Data Scientists and Product Managers using this data to identify new opportunities and test out new ideas.  

What have you done and what do you know? 

You have 6+ years of experience and proficiency building data pipelines in batch and/or real-time settings to support a variety of use cases. Some of our data sources are small (e.g., sales at Netflix House), and some are enormous (e.g., social media feeds). Our stack is Spark, Flink, Iceberg, Kafka - experience with these specific technologies is helpful but not strictly required.

You are proficient in Python and/or Scala for scripting, automation, and data orchestration frameworks, and you can write complex SQL (any variant) for ad-hoc and recurring workflows. You strive to write elegant and maintainable code, and you're comfortable picking up new technologies.

You understand how to model data efficiently for reporting and metrics, and how to organize data for scale and fast retrieval.

You have experience sourcing and modelling data from application APIs and event streams.

You have experience converting business requirements into data engineering workstreams, enabling insights that empower our colleagues to make better and more informed decisions. 

You have experience mentoring and guiding/unblocking other team members, navigating ambiguity and creating clarity

What will you do?

Fully own critical pipelines and data sets to support variety of use cases in data science and engineering.  

Directly collaborate with stakeholders to understand needs, model tables using data warehouse best practices, and develop data pipelines to ensure the timely delivery of high-quality data.

Creatively explore how to use data to continually add value to Netflix. Translate ambiguous business questions into clear data requirements, and then deliver on them.

Be a bridge between data engineering and the business, enabling insights that empower our colleagues to make better and more informed decisions. 

Build strong partnerships with data scientists, analytics engineers, and machine Learning practitioners to enable research and insight delivery for the business. 

Who are you? 

You work quickly and independently while also collaborating effectively across functions (e.g. with marketing experts, data scientists, product managers). 

You thrive in a fast-paced environment and see yourself as a partner in the business, with the shared goal of moving it forward.

You have a growth mindset and expect the same from your colleagues. You are also curious,  authentic, selfless, determined, and industrious. You generously give and receive candid feedback to grow yourself and those around you. 

You have strong beliefs that are weakly held: you can deliberate and hear all sides of a discussion, and adapt to new perspectives that emerge from it. 

You are a sharp communicator who can break down and explain complex data problems in clear and concise language.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.