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We are seeking talented and passionate Data Engineer to join our growing Data team. In this pivotal role, you will be instrumental in designing, building, and optimizing the critical data infrastructure that underpins innovative creative intelligence platform. You will tackle complex data challenges, ensuring our systems are robust, scalable, and capable of delivering high-quality data to power our advanced AI models, customer-facing analytics, and internal business intelligence. This is an opportunity to make a significant impact on our product, contribute to a data-driven culture, and help solve fascinating problems at the intersection of data, AI, and marketing technology.
Key Responsibilities
Architect & Develop Data Pipelines: Design, implement, and maintain sophisticated, end-to-end data pipelines for ingesting, processing, validating, and transforming large-scale, diverse datasets.
Manage Data Orchestration: Implement and manage robust workflow orchestration for complex, multi-step data processes, ensuring reliability and visibility.
Advanced Data Transformation & Modeling: Develop and optimize complex data transformations using advanced SQL and other data manipulation techniques. Contribute to the design and implementation of effective data models for analytical and operational use.
Ensure Data Quality & Platform Reliability: Establish and improve processes for data quality assurance, monitoring, alerting, and performance optimization across the data platform. Proactively identify and resolve data integrity and pipeline issues.
Cross-Functional Collaboration: Partner closely with AI engineers, product managers, developers, customer success and other stakeholders to understand data needs, integrate data solutions, and deliver features that provide exceptional value.
Drive Data Platform Excellence: Contribute to the evolution of our data architecture, champion best practices in data engineering (e.g., DataOps principles), and evaluate emerging technologies to enhance platform capabilities, stability, and cost-effectiveness.
Foster a Culture of Learning & Impact: Actively share knowledge, contribute to team growth, and maintain a strong focus on how data engineering efforts translate into tangible product and business outcomes.

If you share our love of sports and tech, you've got the passion and will to better the sports-tech and data industries - join the team. We are looking for a Data & AI Architect.
Responsibilities:
Build the foundations of modern data architecture, supporting real-time, high-scale (Big Data) sports data pipelines and ML/AI use cases, including Generative AI.
Map the companys data needs and lead the selection and implementation of key technologies across the stack: data lakes (e.g., Iceberg), databases, ETL/ELT tools, orchestrators, data quality and observability frameworks, and statistical/ML tools.
Design and build a cloud-native, cost-efficient, and scalable data infrastructure from scratch, capable of supporting rapid growth, high concurrency, and low-latency SLAs (e.g., 1-second delivery).
Lead design reviews and provide architectural guidance for all data solutions, including data engineering, analytics, and ML/data science workflows.
Set high standards for data quality, integrity, and observability. Design and implement processes and tools to monitor and proactively address issues like missing events, data delays, or integrity failures.
Collaborate cross-functionally with other architects, R&D, product, and innovation teams to ensure alignment between infrastructure, product goals, and real-world constraints.
Mentor engineers and promote best practices around data modeling, storage, streaming, and observability.
Stay up-to-date with industry trends, evaluate emerging data technologies, and lead POCs to assess new tools and frameworks especially in the domains of Big Data architecture, ML infrastructure, and Generative AI platforms.

At our company, were reinventing DevOps and MLOps to help the worlds greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust our company to manage, accelerate, and secure their software delivery from code to production - a concept we call liquid software. Wouldn't it be amazing if you could join us in our journey?
About the Team
We are seeking a highly skilled Senior Data Engineer to join our company's ML Data Group and help drive the development and optimization of our cutting-edge data infrastructure. As a key member of the company's ML Platform team, you will play an instrumental role in building and evolving our feature store data pipeline, enabling machine learning teams to efficiently access and work with high-quality, real-time data at scale.
In this dynamic, fast-paced environment, you will collaborate with other data professionals to create robust, scalable data solutions. You will be responsible for architecting, designing, and implementing data pipelines that ensure reliable data ingestion, transformation, and storage, ultimately supporting the production of high-performance ML models.
We are looking for data-driven problem-solvers who thrive in ambiguous, fast-moving environments and are passionate about building data systems that empower teams to innovate and scale. We value independent thinkers with a strong sense of ownership, who can take challenges from concept to production while continuously improving our data infrastructure.
As a Data Engineer at our company's ML you will...
Design and implement large-scale batch & streaming data pipelines infrastructure
Build and optimize data workflows for maximum reliability and performance
Develop solutions for real-time data processing and analytics
Implement data consistency checks and quality assurance processes
Design and maintain state management systems for distributed data processing
Take a crucial role in building the group's engineering culture, tools, and methodologies
Define abstractions, methodologies, and coding standards for the entire Data Engineering pipeline.

Were looking for a Data Engineer for the Insight Team to join our Data Group and a new team responsible for developing innovative features based on multiple layers of data. These features will power recommendation systems, insights, and more. This role involves close collaboration with the core teams within the Data Group, working on diverse data pipelines that tackle challenges related to scale and algorithmic optimization, all aimed at enhancing the data experience for our customers.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is everything, its at the heart of everything we do. The Data Group is responsible for shaping the experience of hundreds of thousands of users who rely on our data daily.
The Insight Team monitors user behavior across our products, leveraging millions of signals and time-series entities to power a personalized recommendation and ranking system. This enables users to access more unique and tailored data, optimizing their experience while maintaining a strong focus on the key KPIs that drive the success of our Data Group.
What will you be responsible for?
Develop and implement robust, scalable data pipelines and integration solutions within our Databricks-based environment.
Develop models and implement algorithms, with a strong emphasis on delivering high-quality results.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.

We are making the future of Mobility come to life starting today.
At our company we support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platformsupporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

We are looking for an experienced Senior Data Engineer to join our Data team.
In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
Design and develop high-performance data pipelines and ETL processes to support diverse business needs.
Work closely with business intelligence, sales, and other teams to integrate data solutions, ensuring seamless alignment and collaboration across functions.
Continuously improve our data analytics platforms, optimizing system performance while ensuring a robust and reliable data infrastructure.
Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights.
Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently.

We are looking for a Data Engineer to join our team and play a key role in designing, building, and maintaining scalable, cloud-based data pipelines. You will work with AWS (Redshift, S3, Glue, Managed Airflow, Lambda) to integrate, process, and analyze large datasets, ensuring data reliability and efficiency.
Your work will directly impact business intelligence, analytics, and data-driven decision-making across the
What Youll Do:
ETL & Data Processing: Develop and maintain ETL processes, integrating data from various sources (APIs, databases, external platforms) using Python, SQL, and cloud technologies.
Cloud & Big Data Technologies: Implement solutions using PySpark, Databricks, Airflow, and cloud platforms (AWS) to process large-scale datasets efficiently.
Data Modeling: Design and maintain logical and physical data models to support business needs.
Optimization & Scalability: Improve process efficiency and optimize runtime performance to handle large-scale data workloads.
Collaboration: Work closely with BI analysts and business stakeholders to define data requirements and functional specifications.
Monitoring & Troubleshooting: Ensure data integrity and reliability by proactively monitoring pipelines and resolving issues.
Data Modeling: Design and maintain logical and physical data models to support analytics and operational needs.

Were looking for a Data Engineer to design and implement high-scale, data-intensive platforms, research and develop algorithmic solutions, and collaborate on key company initiatives. You will play a critical role within our core data teams, which are responsible for managing and optimizing our fundamental data assets.
Where does this role fit in our vision?
Every role at our company is designed with a clear purposeto integrate collective efforts into our shared success, functioning as pieces of a collective brain. Data is at the heart of everything we do. Our data engineers are responsible for building and maintaining the core products that power our business. The data teams own and manage the pipelines that generate our assets, with a strong focus on optimizing key company KPIs.
We leverage cutting-edge technologies to build and scale our data infrastructure. In this role, you will work closely with Data Scientists and Data Analysts on a daily basis, collaborating to develop innovative data solutions that drive business impact.
What will you be responsible for?
Solve Complex Business Problems with Scalable Data Solutions
Develop and implement robust, high-scale data pipelines to power our core assets.
Leverage cutting-edge technologies to tackle complex data challenges and enhance business operations.
Collaborate with Business Stakeholders to Drive Impact
Work closely with Product, Data Science, and Analytics teams to define priorities and develop solutions that directly enhance our core products and user experience.
Build and Maintain a Scalable Data Infrastructure
Design and implement scalable, high-performance data infrastructure to support machine learning, analytics, and real-time data processing.
Continuously monitor and optimize data pipelines to ensure reliability, accuracy, and efficiency.

Were building the future workforce of Technology organization, while working tightly with domain owners and top management to define what per-role excellence means, leveraging data from development tools to help infer proficiency levels, providing tailored development plans and training & learning material, and harnessing the individuals themselves for their professional and personal development.
Responsibilities:
Design, implement, and maintain the complete data flow, from extraction to visualization using external tools Work within a product team where solutions are collaboratively proposed. You will be expected to translate requirements into technical designs and implement them as part of large-scale data engineering solutions Utilize various Machine Learning models to explore data, collaborating with cutting-edge Big Data tools and techniques Collaborate with various stakeholders to plan, design, develop, TEST and maintain extraordinary features Collaborating with a team of skilled developers to develop high-traffic, cloud-based applications.

We are looking for a brilliant, quick learner Data Engineer for our data engineering team - an independent, logical thinker who understands the importance of data structuring for macro-business decisions.
The position combines high technical skills with a business orientation. It involves working closely with the analysts and the R&D team and directly affecting the company's cross-department decisions. Our Data Engineer should be able to speak in technical and practical terms and, more importantly, lead from one to the other while dealing with challenges and creating them to make our team even better.
Roles and Responsibilities:
Creating and structuring end-to-end data pipelines and ETLs in light of business requirements: from the source to the analyst's hands, enabling them the ideal conditions to make smart and data-driven business decisions.
Cracking top industry data challenges while initiating and building creative technical solutions- in-house Device Graph, Server-to-Server to multiple systems, Privacy challenges, Online-to-Offline, and more.
Deep understanding of the business needs, technical requirements, and the companys roadmap, translating it into custom-made data solutions and scalable products.
Craft code following best practices to ensure efficiency while integrating CI/CD principles.
Writing multi-step scalable processes from more than 50 data sources- Marketing, Operations, CS, Product, CRM, and more, tying them up to a valuable and useful source of insights for the analysts.
Understanding data challenges and weaknesses, and managing high standards, monitoring, and reliability processes.