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Required Senior Data Engineer - Big Data
Our Core Data Platform team:
We're a leading force in the ad tech industry, revolutionizing how brands connect with their audiences.
Our platform processes billions of ad impressions daily, generating massive datasets that drive our core business.
We thrive on innovation and seek a Data Engineer to help us build and scale the data infrastructure that powers our insights and analytics.
This is a unique opportunity to work with cutting-edge technologies and make a direct impact on our products.
What will you do?
As a Big Data Engineer, you'll be a key part of our data platform team, responsible for designing, building, and maintaining robust and scalable data pipelines. You'll work closely with data scientists, analysts, and server side engineers to ensure our data is reliable, accessible, and ready for analysis. Your expertise will be crucial in expanding our data warehouse and data lake capabilities, enabling us to deliver next-generation ad tech solutions.
Your mission will be to:
Develop and Optimize Data Pipelines: Design, build, and maintain ETL/ELT pipelines using Apache Spark to ingest, process, and transform large-scale datasets from various sources.
Manage Cloud Infrastructure: Architect and manage our data infrastructure primarily on Google Cloud Platform (GCP) or Amazon Web Services (AWS). This includes services like BigQuery, S3, GCS, EMR, and AirFlow.
Enhance Data Storage: Improve and manage our data warehouse and data lake solutions, ensuring data quality, consistency, and accessibility for business intelligence and machine learning applications.
Collaborate and Innovate: Partner with cross-functional teams to understand data needs and implement solutions that support new product features and business initiatives.
Ensure Data Integrity: Implement monitoring, alerting, and logging systems to maintain data pipeline health and ensure data accuracy.

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.
Working with this enormous volume of data begins with massive ETL pipelines built using cutting-edge technologies such as Kafka, BigQuery, Airflow, S3, PostgreSQL, Athena, SQS, Redis, and especially Spark. We are big believers in working with the right tool for the right job, including programming languages. We run a truly polyglot shot with Scala, Python, Go and Node being especially common here . The extreme growth rate of our data and client base means that solutions need to be designed to handle 10X growth or more.
What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development
Improve the scalability and performance of existing data pipelines
Delve into existing pipelines and business logic, target weaknesses and add functionality
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible

We are looking for a Data Engineer to join our usage metering & billing platform team! with a strong background in writing ETLs and complicated data processing pipelines. Youre deeply familiar with modern data processing stack (especially Spark, Hadoop and Airflow), have a strong problem-solving attitude and, most importantly, youre passionate about understanding the business side of the platform. Our platform engineers have an end-to-end understanding of the data our products generate and the commercial models and data structures in which they fit.
Working with this enormous volume of data begins with massive ETL pipelines built using cutting-edge technologies such as Kafka, BigQuery, Airflow, S3, PostgreSQL, Athena, SQS, Redis, and especially Spark. We are big believers in working with the right tool for the right job, including programming languages. We run a truly polyglot shot with Scala, Python, Go and Node being especially common here . The extreme growth rate of our data and client base means that solutions need to be designed to handle 10X growth or more.
What youll do:
Develop end-to-end ETLs and data infrastructure features from data processing logic to database choice and implementation through to API development
Improve the scalability and performance of existing data pipelines
Delve into existing pipelines and business logic, target weaknesses and add functionality
Mentor, advise, and work collaboratively within the Biz Data & Dev group, with other development teams, and with all other business teams of the company
Continuously learn and follow new technologies both for personal growth and to ensure we are making the most informed technology choices possible

Responsibilities
Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
Leverage Databricks and other modern data platforms to manage, transform, and process data
Collaborate with software teams to understand data needs and ensure data solutions meet business requirements.
Optimize data processing workflows for performance and scalability.

Experienced Data Engineer? Excellent team player?
Come join a great team to overcome meaningful cyber challenges!
Our Data Solutions Group is looking for an exceptional Python developer with Data Engineering experience.

We're looking for a Product Manager to own all of data export products end-to-end. This is a hands-on role with high customer exposure: you'll work directly with enterprise clients to understand their data access needs, partner closely with internal stakeholders across the organization, and ship improvements across multiple product surfaces in parallel. If you thrive on juggling priorities, communicating clearly across audiences, and turning customer feedback into shipped products, this role is for you.
What you'll do:
Own all of data export products throughout their lifecycles, from discovery and definition through delivery, adoption, and iteration
Partner directly with enterprise customers and internal stakeholders to understand data export pain points and translate them into clear requirements
Prioritize effectively across multiple product surfaces and competing stakeholder needs
Drive cross-functional alignment with engineering and business teams to deliver high-quality features on time
Define and communicate product roadmap, trade-offs, and decisions clearly, both to internal teams and customer-facing audiences
Continuously improve usability, reliability, and documentation based on customer feedback and usage data
Strengthen and expand data export products as the foundation for customers' AI and advanced analytics initiatives by ensuring we deliver the right data, in the right format, at the right cadence

Were looking for a Principal Backend & Data Engineer to own and evolve the core data-intensive backend architecture of our AI platform. This is a senior individual contributor role with broad architectural responsibility and deep hands-on impact.

You will be a technical authority in building scalable, high-performance backend and data systems that power our AI research engine - working closely with AI scientists, platform engineers, and product leaders. Beyond implementation, you will define technical direction, set engineering standards, and influence how we build and scale data-driven AI systems across the organization.

What Youll Do
Architecture & Technical Ownership

Own the architecture of core backend and data systems that support large-scale, AI-driven computation and inference.
Design and evolve high-performance analytical processing layers handling complex data workloads at scale.
Make and drive long-term architectural decisions across backend, data, and AI integration domains.
Define standards and best practices for performance, scalability, reliability, and data correctness.
Backend & Data Engineering

Design, implement, and optimize data-intensive backend services using Python.
Build and evolve analytical compute pipelines using technologies such as Polars, DuckDB, AirFlow, Iceberg, Spark and other ingestion and processing frameworks.
Collaborate closely with AI scientists to productionize algorithms and embed advanced intelligence into the platform.
Platform & Infrastructure

Architect and maintain containerized systems using Docker and Kubernetes.
Ensure systems are observable, debuggable, and operable in production environments.
Drive performance tuning and cost-efficiency across compute-heavy workloads.
Technical Leadership

Act as a technical authority and thought leader within the engineering organization.
Mentor senior engineers through design reviews, architectural guidance, and hands-on collaboration.
Serve as a force multiplier by unblocking complex technical challenges and raising the overall engineering bar.