Data Solutions Architect Jobs

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Ready to level up your career? Join PlayStation as a Senior Software Engineer focused on Platform Data Reliability and Automation and help drive innovation at the forefront of interactive entertainment. You’ll be part of a world-class engineering team focused on building seamless, scalable experiences for millions of players around the globe. At PlayStation, we’re known not only for delivering exceptional gaming experiences but also for fostering a top-tier engineering environment centered on innovation, creativity, and technical excellence . We welcome passionate engineers who thrive on solving complex problems and are aligned with our vision of shaping the future of play. Role Overview: We are seeking a Senior Software Engineer (Platform Data Reliability & Automation) to play a critical role in building, automating, and operating scalable data platforms with a strong emphasis on Infrastructure as Code (IaC) and cloud technologies . This role focuses on the reliability and automation of NoSQL, Streaming, and Caching services across AWS and GCP environments. You’ll design robust automation frameworks, ensure high availability, and partner with product and platform teams to deliver resilient, highly available infrastructure supporting billions of transactions a

Our Mapping team is responsible for building the algorithms and tools necessary to keep Zoox vehicles well calibrated, always aware of their location in the world, and aware of their environment. Without precise calibration, localization, and mapping, our vehicles would be at a disadvantage in perceiving and reasoning about the surrounding world, and this is therefore foundational to enabling results from many other teams across Zoox. This work is critical to scaling autonomous driving safely and reliably. We are looking for engineers who are ambitious and excited about helping Zoox achieve its goals of delivering autonomous mobility. The Road Network Interface team owns road network data definition and data products for all consumers, including developer workflows, in-cluster training jobs, and on-vehicle real-time access. We are seeking a Software Engineer to develop the geometry algorithms behind these data products and the interfaces consumers use to access them - including network topology, road network data format, and validation. In this role, you will... Develop and maintain the geometry algorithms that power our map data interfaces. Implement and maintain key parts of our mapping data format, validation frameworks, post-processing pipelines, and interfaces consumed by downstream customers. Collaborate with cross-functional teams across Zoox to ship features and grow the APIs that downstream consumers depend on. Create design documentation, test plans, and other supporting artifacts for the work you ship. Contribute to all phases of the software development cycle, including prototyping, requirements capture, design, implementation, and validation. Qualifications Bachelor's or higher in Computer Science or related field 3+ years of relevant industry experience Proficiency in C++ Strong

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team Engineers on this team build our rules-based calculation engine for processing sales commissions. This might sound simple if you have never been exposed to sales compensation plans, it is not. We are low on meetings and high on accountability. Most of the team is in the EST time zone, with a few located in PST and Central as well. We are still evolving many areas of the platform, which means there is meaningful room to improve the design, reliability, and scalability of the systems we build. What you’ll be doing Reporting to the Manager of Data Platform, you will play an important role in the evolution of our Spark-based data platform. You’ll design and build data-rich platform capabilities, contribute to system design discussions, and help ensure our data systems remain reliable, maintainable, and scalable as Forma grows. As a Senior Engineer, Data Platform, you are expected to operate with strong ownership and sound technical judgment. This includes identifying risks in the work you own, surfacing edge cases, asking thoughtful questions, and proposing improvements that strengthen the quality and reliability of the platform. You will: Design, build, and improve Spark-based data pipelines and platform services. Work with complex data models representing sales compensation plans, hierarchies, relationships, and enterprise datasets. Build reliable, deterministic data systems that customers and internal teams can trust. Improve testing, observability, data quality,

InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond. At InMobi Advertising , you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Product Management at InMobi: We offer an opportunity to have immediate impact with the company and our products. You shall be working at the cutting edge of technology connecting various

The Predictive Analytics Data Scientist is responsible for designing, building, and optimizing AI-driven predictive models that enhance business intelligence, risk management, and operational efficiency. This role will focus on end-to-end execution, from data collection and model development to deployment and monitoring, ensuring AI models drive actionable insights for demand forecasting, process automation, and business optimization. Source: Adani Group | Job ID: 44281

The Predictive Analytics Data Scientist is responsible for designing, building, and optimizing AI-driven predictive models that enhance business intelligence, risk management, and operational efficiency. This role will focus on end-to-end execution, from data collection and model development to deployment and monitoring, ensuring AI models drive actionable insights for demand forecasting, process automation, and business optimization. Source: Adani Group | Job ID: 44282

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI products so our customers can use deep data insights to improve their business. We are the Data Visualization team, a core part of the AI/BI organization. Our mission is to enable everyone in an organization to make intelligent business decisions informed by the best data available. We empower business teams via self-service analytics, helping them author high-quality visualizations and dashboards using our AI-first authoring experience. We own the visualization library, the dashboarding canvas, and the agentic authoring workflows that bridge the gap between complex data and actionable insights. We are seeking a dedicated Engineering Leader for our Data Visualization team in Bellevue. This team is responsible for the entire life cycle of visual insights: from the underlying visualization framework (using technologies like React and Vega-Lite) to building advanced features like field variables, drill-downs, and AI-driven chart generation. You will report directly to the Senior Manager of Engineering. The Role Lead a Talented Team: You will lead a high-performing engineering team in Bellevue focused on revolutionizing how users visualize data with AI/BI Dashboards. Talent Development: You will oversee the sustained recruitment of top-tier frontend and visualization talent and foster a culture of mentorship and professional growth. Strategic Execution: You will build processes to implement the AI/BI product vision, focusing on "BI Takeout" initiatives to replace legacy tools with superior Databricks-native experiences. Operational Excellence: You will ensure the visualization platform is not only feature-rich but also high-performing, reliable, and easy to operate. Technical Stewardship: You will m

About the Role The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. Key Responsibilities Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. Drive architectural decision

HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree. Our platform is trusted by over 2,500 of the world’s most innovative companies to build strong engineering teams ready for what’s next. Software has entered an era where humans and AI build side by side. As this shift accelerates, the definition of strong technical talent is changing. We give companies better ways to identify and invest in next-generation skills. People at HackerRank care deeply about the impact of their work and sweat the small details so our customers can be wildly successful with products they genuinely love to use. We move with urgency and believe great outcomes come from high standards. About the role We are looking for a Senior AI Data Operations Manager to own and run our end-to-end LLM model data creation pipeline from sourcing and managing vendors, to coordinating with engineering teams to evaluate model performance to closing the loop by creating targeted data for edge cases ensuring the data our models train on meets the highest quality standards. This role will manage the end-to-end AI data pipeline across 10+ AI features spanning multiple products on our platform This is a cross-functional operations role that sits at the intersection of ML, product, and operations management. You will be the connective tissue between our machine learning engineers, internal annotators, and external vendors, translating technical requirements into actionable data creation workflows and ensuring every batch of data that reaches our models is accurate, well-annotated, and fit for purpose. Critically, you will also drive automation across the pipeline, designing and deploying AI agents that eliminate manual bottlenecks and make the entire operation smarter over time. What you will do Own the full AI feature development lifecycle, from sourcing data to quality management and relationship building at scale. Design an

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma's platform helps teams bring ideas to life — and Data Science is central to how we measure, improve, and scale it. We're on a mission to make data self-serve for every Figmate: moving from a world where every data question requires filing a request to a DS or DE, to one where anyone can ask a question in plain language and get a trustworthy answer in minutes. We're hiring Figma's first dedicated Technical Program Manager for Data Science to own that mission — driving our multi-phase Self-Serve Analytics program from semantic layer expansion through the Figma Data Assistant, while building the operational foundation for a growing DS org. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Own end-to-end program delivery for Figma's Self-Serve Analytics initiative that includes semantic layer expansion, Slack bot launch, automated eval framework, and the Figma Data Assistant Coordinate delivery across Data Engineering, DS ICs, Security, IT, and business stakeholders (Sales, Product, Finance, Research) to expand self-serve data coverage and drive adoption Lead the governance and security work stream: work with Security and IT on LLM data access policies, PII guardrails, access controls, and LLM provider approvals Drive adoption and change management — build champion networks, run training programs, and meet Figmates where they work (Slack, Notion) to shift from request-based to self-serve data culture Build and maintain

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We're looking to advance how OpenAI builds and understands pretraining data at scale. You'll treat data quality and curation as core research problems: developing new methods to select, combine, and transform data; creating datasets that improve model capabilities; and designing rigorous experiments to understand how data choices and interventions affect model learning and downstream behavior. You'll work closely with frontier models and web-scale data to build evidence for which approaches work and why, then translate successful research into scalable data processing pipelines We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing multimodal data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We’re looking to advance how OpenAI prepares, curates, synthesizes and understands multimodal data at scale. You’ll work on research and production problems like synthesizing multimodal content (images, audio, and video) and their supervisions, improving noisy data pipelines, building better quality filters, using models to automate data prep, and measuring whether changes in the dataset improve model performance. We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right multimodal data problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Experience with multimodal learning, audio, vision, video, synthetic data, or data-centric ML. Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of

About Us What if your work could drive change in a globally established industry, shaping processes that touch every corner of the world? At Forto, we are at the forefront of change, harnessing the power of AI to revolutionise logistics. We want to reinvent digital supply chains to be transparent, frictionless and sustainable. From day one, our mission has been to simplify global trade – creating a seamless and efficient logistics process. Your role & Mission As Data Director here at Forto, you will be responsible for creating a unified data organisation consisting of Data Science, Data Analytics and Data Engineering. You will dramatically raise the profile of data across the business, partnering with stakeholders in a number of domains to assess and support their data needs. You will own and implement a company wide data strategy, prioritizing competing demands into one cohesive and well understood approach. What you will do Be responsible for the teams (each with their own manager/technical lead) that own the 3 “pillars” of data at Forto: Data Engineering, Data Analytics and Data Science, bringing them into a unified org whilst also encouraging and respecting their specialised skills Ensure that the Data org operates a Centre of Excellence, supporting and educating the “customers” of data across the business. Break down siloes and form strong working relationships with stakeholders. Define and shape a data strategy fit for purpose across our analytical and agentic business needs. Own data governance and quality. Establish the policies, standards, ownership model, and forums that make data trustworthy. Manage day-to-day compliance with GDPR and emerging AI regulation, and set practical guardrails for data and AI use. Sponsor the data platform. Work with engineering and architecture to maintain a reliable, performant, cost-aware platform across ingestion, storage, transformation, BI, and ML. Make build/buy/partner recommendations and manage key vendor relationsh