דרושים » תוכנה » Data Tech Lead

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.

We are seeking a highly experienced and visionary Director, Data &
Analytics to lead our data organization. Reporting directly to the VP of Data, GRC, IT, and
Security, you will be responsible for defining and executing; data strategy, ensuring the
reliability, scalability, and impact of our data assets. You will lead five critical domains: BI
Engineering, Data Engineering, Data Platform, BI Product, and BI Labs (Data Science),
fostering a culture of data excellence, innovation, and partnership across the company.
This role requires a unique blend of deep technical expertise, strong leadership capabilities, and
a keen understanding of how data can drive business value in a fast-paced, data-intensive
environment.
What will you do?
Strategic Leadership: Develop and execute a comprehensive data strategy aligned with ' business objectives. Identify emerging data trends and technologies, and drive their adoption to maintain a competitive edge.
Team Leadership & Development: Lead, mentor, and inspire five diverse teams (BI Engineering, Data Engineering, Data Platform, BI Product, BI Labs), comprising talented engineers, analysts, product managers, and data scientists. Foster a high-performance culture, promoting continuous learning, collaboration, and career growth.
Data Engineering & Platform Ownership: Oversee the architecture, development, and maintenance of ' core data infrastructure, including data lakes, data warehouses, ETL/ELT processes, and real-time data pipelines. Ensure data quality, availability, and governance across all data assets.
Business Intelligence & Analytics Enablement: Drive the development of robust BI solutions, semantic models, and reporting infrastructure that empower business users with actionable insights.
Data Science & Advanced Analytics: Guide the BI Labs team (Data Scientists) in applying advanced analytical techniques, machine learning, and statistical modeling to solve complex business problems, identify business opportunities, and promote AI for predictive analytics .
Cross-Functional Collaboration: Partner closely with engineering, product, R&D, sales, marketing, and finance teams to understand their data requirements, deliver impactful data solutions, and evangelize data-driven decision-making across the organization.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

We are looking for a Data Engineering Lead to join our Platform Group at our company. In this role, you will drive the development of scalable data pipelines and infrastructures that are crucial to our platforms success. You will collaborate across departments, and innovate to ensure our data ecosystem is robust, secure, and optimized for growth.
As a Data Engineering Lead at our company you will...
Architect and develop data pipelines Lead the design and implementation of data pipelines that support our company's platform, ensuring high data quality, security, and governance. Introduce new tools and technologies to enhance data workflows and integration
Develop a strategic roadmap that outlines key engineering solutions to support our platforms scalability and performance, aligned with our company's overall vision and objectives
Collaborate across teams Work closely with internal teams including DevOps, BI, Product, and development groups to ensure seamless data integration and drive data-driven decision-making across the organization
Establish data guidelines and documentation Define best practices for data generation, consumption, and management within the platform. Create thorough documentation for all data processes to facilitate clear communication and future maintenance.

Were looking for a Senior Data Product Manager to lead the strategy and design of B2B data products that empower our companys sales, marketing, finance, and customer success teams with intelligent, insight-driven tools. This role is key to transforming commercial and customer data into trusted, high-quality, and meaningful Data & AI solutions that unlock business growth, optimize the customer journey, and enable AI-powered decision-making.
You will partner with business & data professionals stakeholders to understand their data needs and design platforms & solutions that drive business value, leveraging cutting-edge Data & AI technologies. This is an opportunity to shape the future of data and AI at our company and make a lasting impact.
As a Senior Data Product Manager in our company you will
Own the strategy and roadmap for commercial-facing Data & AI products, delivering actionable insights across the customer journey to support demand generation, sales pipeline optimization, customer success, and account growth.
Translate business goals and analytical needs into clear data product and platform requirements that support our companys evolution into a truly data-driven organization.
Turn account data from across the B2B commercial funnel into intuitive tools, dashboards, and data services that help teams make smarter decisions and identify revenue opportunities.
Partner with AI and engineering teams to build GenAI applications that assist sales reps and CS managers with contextual, real-time recommendations, customer insights, and next-best-actions.
Define and drive the structure for core business entities such as accounts, products, and usersensuring consistency and clarity across all data products through strong master data foundations.
Collaborate with data governance, privacy, and legal stakeholders to ensure that data products are compliant, secure, and high-quality, while building confidence in the data across the business.

We are looking for a highly skilled and versatile ML Data Analyst to join our growing BI & Analytics team. This hybrid role combines business intelligence development, data analysis, and machine learning ideal for someone who thrives at the intersection of data, technology, and business strategy.

Responsibilities:
Lead complex, end-to-end analytical projects, collaborating with stakeholders across Marketing, Sales, Product, Finance, and other teams.
Design and develop BI dashboards and reports, including business funnels and KPI tracking, to support data-driven decision-making.
Analyze business data to uncover actionable insights and drive strategic initiatives.
Develop and deploy machine learning models to support forecasting, segmentation, and other business use cases.
Communicate findings and recommendations to influence strategic decisions across the organization.

e're seeking a highly analytical, curious, and proactive Data Analyst to join our dynamic team. This isn't just a data-crunching role; it's a strategic partnership. You will be the crucial bridge between raw data and executive-level decision-making, directly influencing the strategies that drive success for our publisher network. You'll translate intricate datasets into compelling narratives, helping our senior leadership understand market trends, optimize performance, and identify growth opportunities across our diverse portfolio.
What will you do?
Imagine starting your day scanning key dashboards, then quickly diving into granular data perhaps analyzing a publisher's recent engagement metrics or pinpointing why specific content underperformed. You'll spend significant time in SQL, pulling from various sources to answer urgent executive questions about monetization strategies or partnership proposals, transforming raw data into actionable insights.
A significant part of your role involves crafting compelling "data stories" for non-technical leadership. You'll prepare and present findings directly to VPs or the C-Suite, guiding them through complex analyses of network performance, explaining contribution and trade-off nuances of specific events, and helping shape major strategic initiatives. You're constantly thinking about how to empower executives with timely, impactful data for the future of our publisher network.
Translate complex data into clear, concise, and compelling narratives and strategic recommendations.
Perform deep-dive analysis on network performance and marketplace behavior, impacted both by demand and supply.
Design, build, and maintain interactive dashboards and reports for executive consumption.
Present findings and insights directly to executive leadership, articulating technical concepts simply.
Proactively identify trends, opportunities, and risks within our publisher network.
Collaborate with sales, operations, and product teams to integrate data-driven approaches.

We are seeking a skilled and passionate Machine Learning Engineer who combines strong software engineering expertise with a deep understanding of data science and machine learning. In this role, you will be instrumental in developing and improving our ML systems, ensuring that both the underlying infrastructure and the algorithms powering our models are optimized for performance and scalability.
You will collaborate closely with cross-functional teams, including data scientists and software engineers, to implement end-to-end machine learning models that drive impactful business outcomes. Additionally, your work will ensure the continued improvement of our ML platform, which supports algorithmic work across the company.
What will you do?
As a Senior Machine Learning Engineer, your mission will be:
Improve existing ML library & tools allowing to explore and analyze more and more data and provide accurate feedback on the activities.
Create, design, develop, test and monitor your code in production autonomously and reliably.
Design, develop, and implement ML models and algorithms with a focus on robustness, performance, and scalability.
Collaborate with data scientists to identify and apply effective machine learning techniques and strategies for improved system performance.
Mentor other team members to improve their autonomy and Software Engineering skills.
Collaborate with variety of teams for production cases to develop services from design to production.
Make sure the software is in good hands by writing, running and automating tests (unit, functional, load...).
Keep up to date with the latest Machine Learning technologies to make sure we constantly improve our ML system.

We are looking for a highly skilled Data Analyst with strong technical expertise and business acumen to join our growing BI & Analytics team.

Responsibilities:
Lead complex, end-to-end analytical projects, collaborating with stakeholders across Marketing, Sales, Product, Finance, and other teams.
Design and develop BI dashboards and reports, including business funnels and KPI tracking, to support data-driven decision-making (define the structure and logic of new DWH tables as needed).
Analyze business data to uncover actionable insights and drive strategic initiatives.
Communicate findings and recommendations to influence strategic decisions across the organization.

we are seeking a data-driven and strategic Cloud FinOps Analyst to enhance our cloud cost visibility, drive cost efficiency, and influence strategic decision making across our engineering organization. In this role, you will play a key part in building and maintaining actionable insights into cloud usage and spend, collaborating with engineering, finance, and product teams to shape a data-informed FinOps practice that supports scale and sustainability.
As a Cloud FinOps Analyst at our company, you will...
Build and maintain cloud cost and usage visibility, providing summaries and detailed usage statistics for resources across the public clouds.
Analyze cloud cost and business data, and propose solutions to problems using advanced analysis methods.
Collaborate with the development and finance teams on cost optimization, budget, forecasting, and showback.
Build a strong correlation between cloud cost and the business usage data represented in a unit economics model.
Develop and track key metrics and performance indicators to evaluate and maintain cloud spend health.
Create real-time alerts based on the data models to identify anomalies in the cloud spend.
Effectively use cloud cost management tools.
Support cloud tagging strategies and ensure accurate cost attribution across teams and products.