Senior Data Engineer 5

• 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

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.

About Data Science and Engineering

Data Science and Engineering (DSE) is a key pillar of Netflix’s data-driven strategy, using data, analytics, experimentation, models and consumer insights to support decision-making. The organization focuses on data engineering, metrics, analysis, dashboards, experimentation and analytics, while developing models and algorithms for internal decision support.

About Data Engineering

Data Engineering at Netflix focuses on building efficient data-processing systems and modelling data for analytics. Solutions range from batch pipelines powering business metrics to real-time services supporting core product features. Data Engineers work with large distributed systems and collaborate closely with business, engineering and data science teams.

Netflix is hiring for the first time for the Data Engineering organization in EMEA across several teams.

System Insights & Productivity Metrics

The SIPM team is a new, startup-like group focused on measuring system insights and developer productivity across Netflix. The team builds foundational metrics and data pipelines, with plans to expand into areas such as measuring GenAI ROI.

The role involves working with productivity leaders and product managers to turn business requirements into data engineering projects, track and analyze metrics, address data quality issues and build reliable insights. It is suited to someone who enjoys ambiguity, building from scratch and having a tangible impact on engineering efficiency.

Conversation, Marketing & Fandom Data Engineering

This team builds and manages data engineering pipelines supporting Netflix’s marketing, fandom and global events. You will architect pipelines that ingest data from multiple sources and turn it into insights supporting marketing and fandom decisions.

Security Data Engineering

The team develops data products providing insights into security, fraud and technology risks across customer accounts and internal systems. The role supports security teams in detecting and mitigating risks across Netflix’s large and complex cloud infrastructure.

Member Data Engineering

This team develops data products that measure the Netflix product experience, track key KPIs and support innovation through A/B testing. You will work with Engineering teams on client and server logging, collaborate with Data Scientists and Product Managers, and use data to identify opportunities and test new ideas.

,[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. ] Requirements: Python, ETL, Spark, SQL, Data pipelines, Use cases, Flink, Kafka, Scala, Data engineering, scala Additionally: Private medical package, Life insurance, Conferences, International environment, Work Not Drive, Employee Giving, Employee Assistance Program, Family Forming & Reproductive Health, PPK, Flexible working hours, In-house trainings, ESOP, Psychological support, Modern office building, Team events, Free lunch, Free parking, Mobile phone, Free snacks and beverages, Bike parking, No dress code, Shower, Free breakfast.