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We are looking for an experienced DevOps Data Infra Engineer to join our growing team. As a Data Infra Engineer, you will play a critical role in setting up, optimizing, and maintaining our data & analytics infrastructure. You will work closely with the development and Security teams to ensure the reliability, scalability, redundancy, and security of our data infrastructure platform.

The ideal candidate is passionate about big data, loves working with cutting-edge technologies, and thrives in a collaborative environment.

What you will do:

Design, implement, and manage scalable, highly available databases for both transactional, real-time use as well as backend analytics and big data.

Build, design, and maintain data processing pipeline infrastructure used by our various applications

Develop and maintain CI/CD processes for automating seamless changes to data infrastructure, including data migrations and database upgrades

Work closely with developers to make sure our data infrastructure meets existing and new feature requirements

Work alongside our Security Team to ensure our infrastructure meets rigorous security standards

Ensure the data infrastructure processes adhere to best practices in security and compliance.

We are seeking talented and passionate Senior Data Engineer to join our 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.

Were hiring a hands-on Senior Data Engineer who wants to build data products that move the needle in the physical world. Your work will help construction professionals make better, data-backed decisions every day.
Responsibilities:
Lead the design and development of scalable data pipelines.
Collaborate with Product, Data Science, and Analytics teams.
Build and optimize workflows using Databricks, Spark, Kafka, and AWS.
Implement real-time and batch processing architectures.
Develop and maintain ingestion pipelines from multiple sources.
Manage deployment and performance of data infrastructure.
Use Terraform to manage infrastructure-as-code.
Prepare data for analytics and product-facing use cases.

We are looking for a Senior Data Scientist / Applied AI Researcher with deep expertise in NLP and LLM-based systems, and the ability to operate across the full lifecycle, from problem formulation and research design to production deployment and real-world iteration.
You wont be working on isolated experiments. Youll be part of a multidisciplinary team that owns the system end-to-end and is responsible for how it behaves under real production traffic.
This role requires strong scientific discipline and the maturity to balance innovation with practical constraints.
What youll do:
End-to-End Ownership: Lead AI security solutions from problem formulation and research design through model development, evaluation, and production deployment. Ensure solutions are measurable, reliable, and effective under real-world traffic.
Drive Technical Direction: Take responsibility for ambiguous AI security problems, propose thoughtful approaches, and drive structured experimentation and deep model analysis.
Build for Scale: Design systems that are not only accurate, but scalable, efficient, and robust.
Staying Updated: Continuously explore advances in NLP and LLM-based systems, and critically assess what is worth integrating into a production environment.

our mission is to make the pursuit of creative hobbies simple and fun for all. our top-grossing apps put us on the fast track to building the world's largest consumer subscription service for creative learning. with over a million monthly downloads and hundreds of thousands of daily learners, we're building the ai creative companion for every home.
what data leads do here:
we are looking for a data lead to own end-to-end data -driven business and product analysis. the product data lead impacts all data aspects of the product teams ( data modeling, analytics, tests, visualization, data engineering, ml), influencing critical product decisions.
who you are:
you have product understanding and orientation
you thrive in ambiguity
you turn unstructured reality into actionable models
you are excited when learning something new and applying it
an amazing people-person and team player
you do not shy away from accountability

we are looking for a Staff Data Scientist.
The Data Science department powers core engine by building production-grade algorithmic solutions at immense scale. As a Staff Data Scientist on the Identity team, you will drive the innovation roadmap for our Identity Graph Engine. You will architect, research, and deploy state-of-the-art machine learning models - spanning graph neural networks, transformers, and deep tabular architectures - to solve complex entity resolution and fraud prevention challenges at scale.
What You'll Be Doing:
Drive Identity Graph Innovation: Architect and advance the next generation of our Identity Graph Engine using state-of-the-art graph models, transformers, and machine learning techniques.
Technical Leadership: Define the research roadmap for identity resolution, setting technical standards and guiding complex research projects from initial concept to high-throughput production systems.
Large-Scale Modeling: Build scalable predictive and representation-learning models over massive tabular, sequence, and graph-structured datasets.
Cross-Functional Architecture: Collaborate closely with Data Engineering, Core Software, and Product teams to seamlessly integrate complex ML pipelines into real-time production environments.
Mentorship & SOTA Research: Benchmark and import cutting-edge academic research into practical business solutions while mentoring senior data scientists on modern modeling paradigms.

Required Senior Data Engineer
21679 ID
Role Description:
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

As a AI-Data Engineer, youll take a leading role in building the foundation of our companys Agentic Exposure Management platform: the source of truth that tells a security team what they have, whats actually risky and why, how to fix it, and who is responsible.
Enterprises run their security across a sprawl of cloud and on-prem tools. Making sense of that sprawl is the heart of what we do. Were building a complex data fabric that reconciles data from a hundred different sources, applies sophisticated transformation and enrichment, and turns partial, uncertain signal into one trustworthy model of an organizations real exposure.
Key Responsibilities:
Model the security graph. Design an ontology that spans both the modern cloud and the classical on-prem world, abstract enough to absorb 100+ different integrations under one model, yet rich enough to carry everything needed for decision making. Decide whats an entity, whats an edge, and whats a denormalized attribute, across millions of assets and finding rows.
Own asset identity engineering and reconciliation. Upstream identifiers are uncertain and volatile. Engineer deterministic identity resolution for assets and findings arriving from different vendors.
Build LLM-based and agentic pipelines for data classification, entity extraction, and enrichment, optimizing for cost, latency, and precision in production.
Build the integration factory. Stand up a scalable integration platform that drives down time-to-integration.
Build and maintain complex ETL pipelines handling millions of records: incremental sync, complex correlation, and data quality observability and monitoring.

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data scientists & engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.
The Price Optimization (PO) team is where insights become decisions. We work with large-scale customer data and market predictions - like demand forecasts - to drive revenue management decisions that actually move the needle.
At our core, we build and maintain the decision-making engine. That means designing the data pipelines that bring customer data in, and running it through a price optimization decision model that simulates the market - weighing competition, pricing constraints, inventory availability, predictive models, and each client's unique business policies - to generate the best possible price recommendations. As the final step before recommendations reach the client, quality, reliability, and attention to detail aren't just nice to have. They're everything.
You will lead the team through architecture decisions, development, and deployment of mission-critical systems-while growing and mentoring a high-performing team.
Responsibilities:
Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.
Analyzing existing models and algorithms, researching for new approaches in price optimization.
Design, build and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve our data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data science engineering team.

We are seeking a skilled and motivated Data Engineer with expertise in Elasticsearch, cloud technologies, and Kafka. As a data engineer, you will be responsible for designing, building and maintaining scalable and efficient data pipelines that will support our organization's data processing needs.
The role will entail:
Design and develop data platforms based on Elasticsearch, Databricks, and Kafka
Build and maintain data pipelines that are efficient, reliable and scalable
Collaborate with cross-functional teams to identify data requirements and design solutions that meet those requirements
Write efficient and optimized code that can handle large volumes of data
Implement data quality checks to ensure accuracy and completeness of the data
Troubleshoot and resolve data pipeline issues in a timely manner.

As a Senior Research Scientist, AI & Data Systems at Eon Research, you will conduct applied research at the intersection of AI, data systems, and large-scale storage. you will explore challenging technical problems, publish research in leading peer-reviewed venues, file patents, and translate research breakthroughs into production-ready product capabilities.

This role is ideal for a researcher with a strong publication record, deep expertise in a relevant research area, and experience bringing research into real-world products.

Research Areas
Query Processing and Query Engines: Query optimization and execution over columnar and lakehouse formats, including Apache Iceberg and Parquet, as well as approximate query processing using sketches and synopses.

Storage Systems: Deduplication, compression, and data layout optimization for large-scale storage.

Data Integration and Discovery: Entity resolution, schema matching, table joinability, and data discovery, including the use of LLMs as judges.

Information Retrieval and RAG: Retrieval-augmented generation over enterprise data, including emails, documents, and databases.

LLM Evaluation and Benchmarking: Evaluation frameworks and benchmarks for LLM agents working with enterprise data.

LLMs for Software Engineering: CI failure diagnosis, automated debugging, and program repair.

We are looking for a mid-level Data Engineer, experienced with building data pipelines using Python and Airflow for structured data and relational databases. The ideal candidate is a self-directed learner, takes ownership of the pipelines they build, and cares about data quality as much as feature delivery.





Key Responsibilities:

Own our data pipelines, including maintenance and adding new features.
Take charge of data integrity and completeness, including writing and maintaining tests.
Improve process efficiency and optimize runtime performance.
Own schema design and evolution across our data pipelines.

we are looking for a Data Operations Team Lead.
The Data Engagement team is the connective link between GTM and R&D/Product organizations. The team leads customer and prospect data initiatives using internal tools, and drives product improvements based on patterns and issues analysts identify in their day-to-day work.
What you'll do:
Own execution of the team's initiatives - ensuring efforts are properly resourced, tracked, and delivered within required timeframes.
Play a key role in prioritizing data resources across company-wide efforts, working closely with stakeholders across R&D, Product, Customer Success, and Sales.
Lead and develop a multidisciplinary team of highly skilled analysts.
Build strong partnerships with Product and CS leaders, acting as their trusted data advisor to help achieve shared business objectives.

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards