Director of Analytics Engineering

Mariana Minerals, based in San Francisco, supplies critical minerals for sectors such as energy, AI, and defense. The company integrates industrial expertise with advanced software, automation, and data-driven processes to improve how minerals are sourced, refined, and optimized. Mariana Minerals emphasizes responsible mineral sourcing and supply throughout its operations. Role overview The Analytical Systems Engineer will support laboratory analytical capabilities across multiple locations. This position focuses on developing and refining analytical methods, troubleshooting technical issues, and introducing new instruments and procedures. The role calls for a strong analytical background, hands-on mechanical skills, and adaptability in various lab environments. What you will do Enhance and optimize analytical methods at laboratory sites. Troubleshoot and resolve issues with analytical techniques to ensure reliable data and methods. Lead implementation of new instruments, including ICP-OES, ICP-MS, Atomic Absorption, and related equipment. Create, validate, and standardize analytical workflows and methods. Train laboratory staff on equipment usage, analytical techniques, and best practices. Collaborate with cross-functional teams to improve analytical efficiency and maintain data integrity. Evaluate new technologies and suggest improvements for existing systems. Maintain thorough documentation for methods, SOPs, and technical guidelines. Offer technical support for complex analytical challenges within the organization. Requirements Bachelor’s degree in Analytical Chemistry, Chemistry, or a related scientific field (recent graduates encouraged to apply). Experience with ICP-OES, ICP-MS, Atomic Absorption, or similar analytical instruments is preferred. Solid understanding of analytical techniques, sample preparation, and data interpretation. Strong problem-solving abilities and the capacity to work both independently and as part of a team.

Join Cloudflare as a Distributed Systems Engineer within our dynamic Data Platform team, focusing on Analytics and Alerts. In this position, you will play a pivotal role in building and optimizing distributed systems that power our data analytics capabilities, providing real-time insights and alerts to enhance our customer experience.

Join Cloudflare as a Distributed Systems Engineer focusing on our Data Platform, where you will play a pivotal role in developing analytics and alert systems that enhance our services. You will collaborate with a talented team to design scalable and efficient systems to manage and analyze vast amounts of data. Your work will directly impact the performance and reliability of our offerings, ensuring our customers have the best possible experience.

Join Scale AI’s Finance Analytics and Systems team as a proactive team member dedicated to crafting and enhancing internal tools and AI agents designed to automate workflows within finance and accounting. In this dynamic role, you will collaborate closely with stakeholders across business finance, corporate finance, and accounting to gain insights into their workflows, enabling you to develop systems that facilitate quicker turnaround times with enhanced accuracy. Your responsibilities will include designing data models, prototyping internal tools, and implementing agent-driven workflows utilizing our internal data infrastructure, system integration tools, Scale’s proprietary AI platform, and innovative AI tools. We seek an individual who thrives on tackling complex challenges, is passionate about building systems from the ground up, and excels at translating vague business needs into scalable technical solutions, all while maintaining a strong focus on detail and a thorough approach to validating results.

Join Gusto as a GTM Analytics Engineer and play a pivotal role in driving our analytics initiatives. As a part of our team, you will develop and maintain robust analytics frameworks that empower data-driven decision-making within our go-to-market strategies. You will collaborate closely with cross-functional teams to ensure the accuracy and accessibility of data, while also identifying opportunities for continuous improvement.

Airtable is seeking a talented AI Analytics Engineer to join our dynamic marketing analytics team. In this role, you will leverage advanced analytics and machine learning techniques to derive insights from marketing data, drive strategic decisions, and optimize our marketing initiatives.

Join Airtable as an AI Analytics Engineer, where you'll play a pivotal role in transforming business insights through advanced data analytics and AI technologies. Collaborate with cross-functional teams to develop and implement data-driven solutions that enhance operational efficiency and decision-making processes.

Role Overview Okta is looking for a Senior Analytics Engineer to help shape data-driven decisions across the company. This role focuses on designing and building analytics solutions, improving data architecture, and working with teams from different functions to uncover insights from complex datasets. What You Will Do Design and implement analytics solutions that support business goals Collaborate with colleagues across departments to identify and extract meaningful insights from large data sets Enhance and maintain the company’s data architecture to ensure reliability and scalability About Okta Okta delivers identity management solutions for organizations worldwide. Your work as a Senior Analytics Engineer will help support Okta’s mission to provide secure, seamless access for users everywhere. Locations Bellevue, Washington Chicago, Illinois San Francisco, California

At Perplexity, we believe in harnessing the power of AI to exceed expectations. This role is pivotal in ensuring our data team embodies that philosophy, placing AI at the core of our operations.We seek an exceptional individual with a strong background as a data scientist, analytics engineer, or data engineer. You are the type of professional who understands which metrics hold true significance, can design insightful A/B tests, and delve into data models to uncover discrepancies. Importantly, you recognize that your highest impact opportunity lies in creating AI systems that revolutionize the practice of data science.This is not about developing another text-to-SQL bot or merely producing another dashboard. Instead, you'll create AI agents capable of performing comprehensive analyses autonomously – generating hypotheses, executing queries, interpreting outcomes, and crafting actionable recommendations. Your work will ensure that our entire data warehouse is AI-accessible, enabling any system to query it with precision. You'll engineer self-correcting pipelines that identify and resolve data issues proactively. Your contributions will empower a lean data team to operate with the efficiency of a much larger organization.Join a forward-thinking data team that already integrates AI into its processes, yet recognizes the vast potential that lies ahead. With full support from leadership, we are committed to transforming our initial efforts into a world-class framework: scalable systems, innovative tools, and an AI-first approach that not only elevates our status but also propels the industry forward.What You'll DoEnhance the AI-driven data workflow - Building on existing successes, you will establish repeatable systems and scalable tools that the data team and the broader organization can adopt.Create AI agents for data science - Your focus will be on developing agents that not only handle SQL inquiries but also manage end-to-end analyses: exploring data, formulating hypotheses, executing queries, interpreting results, and delivering actionable insights.Make the data warehouse AI-friendly - Design the semantic layers, context, and retrieval systems that enable any AI platform (internal or external) to query Perplexity's data effectively and reliably.Automate the data lifecycle - Implement self-healing pipelines, automated dbt model creation and validation, and data quality agents that autonomously detect and resolve issues.Deliver AI-enhanced experiment analysis - Develop agents capable of interpreting A/B test results, identifying statistical anomalies, and providing thoughtful insights.

Join Arena Intelligence as an Analytics Engineer!Arena Intelligence is a pioneering platform devoted to assessing the performance of AI models in real-world scenarios. Founded by talented researchers from UC Berkeley's SkyLab, our mission is to advance AI applications through rigorous evaluation and transparency.Each month, millions engage with Arena Intelligence to comprehend the effectiveness of cutting-edge AI systems, and we leverage our community’s insights to foster trustworthy and user-centric model evaluations. Top enterprises and AI laboratories depend on our assessments to gauge real-world reliability, alignment, and impact. Our leaderboards set the standard for AI performance, earning trust from industry leaders and steering global discussions on model reliability.Our dynamic team consists of researchers, engineers, and innovators with backgrounds from prestigious institutions such as UC Berkeley, Google, and Stanford. We prioritize truth, speed, and craftsmanship while maintaining an inclusive environment where passionate minds from diverse backgrounds can excel. Our workplace embodies excellence, energy, and concentration.Role OverviewWe are looking for an experienced Analytics Engineer to build and manage the data infrastructure that supports real-world AI evaluations. You will be responsible for designing and implementing analytics-ready data models, pipelines, and metrics that transform raw user data and votes into valuable insights for our stakeholders.This role is positioned at the intersection of data engineering, analytics, and product development. You will collaborate closely with researchers, product managers, and engineers to define schemas, standardize metrics, and ensure accuracy and scalability of our evaluation data. Your contributions will significantly influence how AI performance is assessed and interpreted across the sector.We seek someone who is passionate about crafting clean, robust data systems, values data integrity, and desires to see their work drive product decisions and benefit our external clients.

Join Airtable as an AI Analytics Engineer and be part of a pioneering team that is dedicated to enhancing our AI & Analytics Platform. In this role, you will leverage cutting-edge technologies to analyze vast datasets and drive insights that inform decision-making processes across the organization. You will work collaboratively with data scientists and engineers to develop innovative solutions that meet our clients' needs.

Earnest builds borrowing solutions that help people take control of their financial futures. The Analytics Engineer II role supports this mission by improving how data is modeled, organized, and delivered across the company. Role overview This position reports to the Senior Manager of Data Platforms and Analytics Engineering. The Analytics Engineer II works closely with Product, Risk, and Analytics teams to ensure data is accessible, reliable, and structured for confident decision-making. What you will do Design and refine data models to support faster and more dependable decisions across multiple business teams. Remove data bottlenecks by providing clean, scalable datasets that analysts can use independently. Support both planned projects and urgent requests, helping business teams operate smoothly. Improve data quality and organization to enable effective analysis and the launch of new products or features. Requirements At least 3 years of experience in analytics engineering, data engineering, or a related field. Strong SQL skills and experience building data models that align with business needs. Familiarity with dbt and modern data warehouse solutions such as Snowflake or Redshift. Ability to collaborate across teams and translate complex data into actionable insights. Curious, proactive, and motivated to solve problems beyond assigned tasks. Preferred qualifications Experience with orchestration tools like Airflow or similar platforms. Background in fintech, product analytics, or high-growth companies. Location This is a remote role based in the United States. Earnest's headquarters are in San Francisco, CA.

About FaireFaire is a revolutionary online wholesale marketplace that champions local commerce, believing in the strength of independent retailers. These retailers are generating more revenue globally than giants like Walmart and Amazon, yet they remain small compared to these corporate titans. At Faire, we harness technology, data, and machine learning to bridge the gap between these vibrant entrepreneurs and the best products from around the world. Our mission is to empower local businesses with the right tools and insights, leveling the playing field against big box and e-commerce competitors.By nurturing the growth of independent businesses, Faire is creating a positive economic impact in communities worldwide. We are on the lookout for innovative, resourceful, and passionate individuals to join us in our quest to revolutionize local shopping. If you share our belief in the power of community, we invite you to be a part of ours.About the RoleAre you enthusiastic about leveraging data and AI to redefine product features for small and medium businesses (SMBs)? If this resonates with you, we want to connect! We are seeking a technical leader to collaborate with Data Scientists, Product Analysts, and Software Engineers to enhance product launches and roadmaps. You will be instrumental in designing and developing data capabilities that drive insights and inform decision-making. This role will put you at the forefront of utilizing AI to enhance productivity and transform analytical engineering processes—streamlining data pipeline development, optimizing data consumption workflows, and automating routine analytical tasks. Your contributions will have a direct impact on company growth and user satisfaction. Join our team of top-tier professionals, work with one of the richest datasets available, and see your efforts translate into real-world applications for SMBs.Join us and contribute to a culture that values data-driven innovation and excellence.

Join Us in Building a Safer World.At TRM Labs, we specialize in blockchain analytics and AI solutions aimed at assisting law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in identifying, investigating, and preventing crypto-related fraud and financial crime. Our innovative platforms leverage blockchain intelligence and AI technology to trace funds, detect illicit activity, and construct comprehensive threat profiles. Trusted by leading organizations worldwide, TRM Labs is committed to enabling a safer and more secure environment for all.Our AI Engineering Team is dedicated to pioneering next-generation AI applications, particularly in the realm of Large Language Models (LLMs) and agentic systems. Our goal is to develop resilient pipelines and high-performance infrastructure that facilitate the swift, safe, and scalable deployment of AI systems.We manage extensive petabyte-scale pipelines, ensuring model serving with millisecond latency while providing the necessary observability and governance to make AI production-ready. Our team actively evaluates and integrates leading-edge tools in the LLM and agent space, including open-source stacks, vector databases, evaluation frameworks, and orchestration tools to accelerate TRM’s innovation pace.As a Senior or Staff ML Systems Engineer – LLM, you will play a pivotal role in constructing and scaling our technical infrastructure for AI/ML systems. Your responsibilities will include:Creating reusable CI/CD workflows for model training, evaluation, and deployment, integrating tools such as Langfuse, GitHub Actions, and experiment tracking.Automating model versioning, approval processes, and compliance checks across various environments.Developing a modular and scalable AI infrastructure stack that encompasses vector databases, feature stores, model registries, and observability tools.Collaborating with engineering and data science teams to embed AI models and agents into real-time applications and workflows.Continuously assessing and incorporating state-of-the-art AI tools (e.g., LangChain, LlamaIndex, vLLM, MLflow, BentoML).Promoting AI reliability and governance while enabling experimentation, ensuring compliance, security, and continuous uptime.Enhancing AI/ML Model Performance and ensuring data accuracy and consistency, leading to improved model training and inference.Implementing infrastructure to facilitate both offline and online evaluation of LLMs and agents.

Role overview OpenAI seeks a Systems Engineer to work directly with network, storage, and systems infrastructure. This position involves hands-on support for the core technology stack, ensuring that essential systems remain performant and reliable. Daily work centers on maintaining and improving the backbone that supports OpenAI's operations. The role addresses both immediate technical issues and ongoing infrastructure needs. Key focus areas Manage and optimize network, storage, and systems components Support the stability and efficiency of core infrastructure Troubleshoot and resolve issues impacting system performance Location This position is based in San Francisco.

About Our TeamJoin the Finance Data team within our CFO organization, where we are dedicated to creating innovative internal data products that enhance analytics capabilities and streamline operations across various business units. Our team is the go-to source for technical expertise on impactful, scalable projects, specializing in financial and transactional data that underpins our daily financial activities.Your RoleAs an Analytics Engineer, you will lay the groundwork for scaling analytics across our organization while promoting best practices in data management as we grow. We are committed to shaping the future of our Finance team.You will collaborate closely with key stakeholders within Finance and across other business units to identify challenges and develop sustainable solutions. Additionally, you will lead projects that create significant business value and foster a robust data culture among Finance teams.We are in search of an experienced engineer with a solid background in managing the entire data stack in high-volume transaction environments, specifically overseeing critical ETL pipelines utilized by non-technical teams. As a versatile problem-solver, you will engage in various Finance domains (e.g., Tax datamart, ERP migration, Procurement automation). The ideal candidate thrives in dynamic settings, adapts swiftly to changing requirements, and confidently navigates through ambiguity. Note that this role does not involve training ML models, nor does it focus on ‘product analytics’.This position is based in San Francisco, CA, operating under a hybrid work model of three days in the office each week. We also offer relocation assistance for new hires.Key Responsibilities:Assess the data requirements of Finance teams, including Revenue, Tax, Procurement, Compute & Infrastructure Accounting, and Strategic Finance, translating these needs into actionable technical specifications.Drive the development of data products and tools that empower stakeholders with self-service capabilities, enabling scalable analytics throughout the organization.Lead the dimensional design process—defining, owning, and maintaining business-facing data marts.

Join Cloudflare as a Distributed Systems Engineer and help us build and maintain our innovative Data Platform. In this role, you'll be working on our Analytical Database Platform, focusing on enhancing data processing and storage technologies to support our global client base. If you are passionate about distributing systems and enjoy solving complex problems, this is the perfect opportunity for you!

Join Mixpanel as a Senior Analytics Engineer and play a pivotal role in transforming raw data into actionable insights. You will collaborate with various teams to design and implement robust analytics solutions that drive data-driven decision-making across the organization.

Join Philo: The Ultimate Streaming Service for TV and Movie Enthusiasts At Philo, we are a passionate team of technology and product innovators committed to revolutionizing the television landscape. By merging state-of-the-art technology with the captivating medium of TV, we are creating the viewing experience we've always desired. This involves utilizing cloud delivery, modern technology stacks, machine learning, and meticulously crafted native app experiences across all our platforms. Our goal is to provide a seamless streaming experience while pioneering next-generation multi-screen and multi-user playback functionalities. The Importance of Data at Philo Data is at the core of everything we do at Philo. It informs our business strategies, enhances our streaming quality, supports product experiments for optimizing user journeys, and simplifies the process for users to discover the perfect content. With over a billion streams delivered annually, our data generates immense value across the organization. Philo's data platform operates at a massive scale, processing trillions of events each year within a petabyte-scale data lake and facilitating thousands of analytical queries that drive decision-making throughout the company. Our Data Engineering team integrates both data engineering and analytics engineering. As a Senior Analytics Engineer at Philo, you will lead the data modeling layer that transforms raw event and application data into reliable, clean data products that the entire company depends on—ranging from metric definitions and dimensional models to a governed semantic layer ensuring consistent metrics for all. You will collaborate closely with data scientists, analysts, and business stakeholders to comprehend their analytical needs and translate them into well-structured, well-documented, and efficient data products using dbt and Snowflake. We are dedicated to delivering a high-quality, trustworthy data platform for the entire organization, employing both cutting-edge technologies and established engineering practices in close cooperation with all departments. Our analytics engineering stack is centered around dbt and Snowflake, enhanced by tools such as Segment, Avo, and BigEye, which facilitate event tracking, data quality, and observability. Recent projects undertaken by our analytics engineers include the development of new models for vital financial data, dbt model design and refactoring, metric definition and governance, cost optimization per query in Snowflake, and the establishment of data quality testing and documentation frameworks. About the Role We are seeking a Senior Analytics Engineer to take ownership of our analytics initiatives...