Pipeline Excellence Director Jobs

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Drive the evolution of Everpure’s enterprise connectivity by designing and deploying robust integration solutions that power our Go-To-Market (GTM) strategy . Collaborating closely with Digital Transformation Group Architects and cross-functional business partners, you will establish the Integration North Star and build scalable middleware pipelines. In this role, you will eliminate data silos, optimize workflow architectures, and directly accelerate business performance across core commercial platforms . WHAT YOU'LL DO Architect & Implement Integration Enablers: Design and build enterprise-grade Boomi integration components (API, EDI, and FLOW) to connect critical enterprise endpoints including Salesforce, SAP, Workday, NetSuite, and Kafka . Optimize Integration Workflows: Conduct technical analysis and re-engineer legacy middleware processes to simplify data flows, lower system latency, and enhance output quality across all GTM operations. Drive Strategic Alignment: Collaborate with Digital Transformation Group Architects to translate business vision into scalable, event-driven, and real-time integration patterns using web services, databases, ETL, and messaging streams . Deliver High-Availability Solutions: Establish operational standards and monitor process performance metrics to ensure seamless, reliable data exchange across global business operations. WHAT YOU BRING Expertise in Boomi & Middleware Ar

The Opportunity This is an exciting time at Enigma. We’re on the cusp of releasing our next generation of small business intelligence products built on years of learnings in the space. We are seeking an experienced Data Scientist to join our Entity Resolution team and help shape the trajectory of these products. Your work will directly impact the accuracy, scalability, and predictive capabilities of our data platform, influencing key business decisions for our customers. The Role Data is at the core of Enigma’s product, which makes data science the beating heart of what we ship. As a Data Scientist on the Entity Resolution Team, you will work in a cross-functional team alongside other data scientists, engineers, and business stakeholders. You will own problems end to end–from raw source data, through models and scalable pipelines, to the customer interface. Your impact will be measured by the contributions you make with your team to improve the accuracy of our data and the value of our product to our customers. What You’ll Do Translate customer goals into working solutions, using large-scale data transformation, sound statistics, and high-quality code. Most of our work is in Databricks (both Spark SQL + PySpark), supported by statistical tooling, and by ML/AI where the problem calls for it. Set a high standard for rigorous analysis and model development, grounded in sound statistical practice, so that results are high-quality and reproducible. Treat data as a reflection of the real world, and develop repeatable strategies for validating results against ground truth. Develop techniques to detect gaps in our data, find the source, and close them in a way that improves the product. Apply a data-focused, first-principles approach to problem solving. We value people who bias toward simple and elegant solutions, but who can implement state-of-the-art models and techniques when the problem requires it What Makes This Role Exciting? Technical challenge : Enigma

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: Multiple years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native:

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

Role Purpose: At Jumio, you will work for one of the market leaders in the global identity verification space that is helping to make the digital world a safer place for everyone. As a Software Development Engineer in the MLOpsTeam, you will develop the blueprint for highly scalable and performant ML model serving. Role Value: As a Software Engineer (SDE III), you will drive the continuous improvement of the infrastructure and applications to manage the lifecycle of ML assets (data, models) to better developer experience and strengthen governance capabilities. Secondly, you will design and implement robust ML infrastructure for model deployment, serving, and optimization. You will work on efficient CI/CD pipelines for ML models and leverage advanced compilers or hardware optimization to maximize inference performance while optimizing costs. We welcome you to challenge us to impact our software development processes and tools. Example Responsibilities: Upgrade ML assets (models, data) management systems for better developer experience and robust governance capabilities Build and optimize model serving infrastructure with a focus on inference latency and cost optimization Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options Implement cost-efficient, enterprise-scale solutions Collaborate in a cross-functional, distributed team for continuous system improvement Work with MLEs, QA Engineers, and DevOps Engineers Evaluate and implement new technologies and tools Contribute to architectural decisions for distributed ML systems Experience and Qualifications : 5+ years of experience in software engineering with Python Experience with model lifecycle management (MLFlow, Weights & Biases or equivalent) Experience with data management ecosystem (quality, transformation, catalog) Experience with ML frameworks, particularly PyTorch Experience optimizing ML models with hardwar

Key Responsibilities Enterprise Data Strategy & Client Engagement: Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. Data Modeling, Design & Engineering: Design and optimize both logical and physical data models to support enterprise-wide systems. Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. Technology Evaluation & Implementation: Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. Team Leadership & Hands-On Management: Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. Ensure project milestones are met through effective resource management and team coordination. Performance, Security & Best Practices: Optimize data storage, retrieval, and processing performance across various systems. Collaborate with security teams to enforce data governance, compliance, and privacy standards. Establish and promote best practices in data management, data engineering, and architecture design. Documentation & Reporting: Develop and maintain comprehensive documentation covering data architecture designs, data flows, integrati

JD : Full Stack with React ,HTML ,CSS 4+ working experience in ReactJs, Html 5, CSS, Responsive design on UI , and Springboot, REST APIs in backend. Experience with Java web application development, Microservices architecture and distributed cloud systems. Experience with REST APIs using Spring boot, Spring data, Spring cloud config, Spring AMQP connector or similar framework in microservices development. Hands on with SQL commands stored procedures. Hands on experience with CI/CD pipelines and setting up various code quality checks in the pipelines. Skills Required UI React JS HTML 5 ,CSS 3 JEST framework Material UI Responsive Design Backend Java/J2ee, Spring MVC, Spring Boot, Micro services Architecture & design Patterns, Docker containers SQL Basic Queries , Stored Procedures AWS EC2/ECS,Lambdas,S3, RDS, SQS

About the Role We are looking for a Senior SAP BW/BI Developer to design, build, and optimize enterprise data warehousing solutions on SAP BW. The ideal candidate has deep hands-on experience across the full SAP BW/BI stack — from data extraction and ABAP development to performance tuning and cross-platform data integration — and can independently own complex data solutions from design through production support. Key Responsibilities Design and develop SAP BW/BI solutions, including data models, extraction logic, and reporting objects to support business analytics needs. Build and maintain data ingestion pipelines from SAP ECC and functional modules including PM, FI/CO, SD, MM, and C4C into SAP BW. Develop, enhance, and debug custom extractors, user exits, and enhancements using ABAP programming. Design and build DSOs (Data Store Objects), InfoCubes, and BEx Queries to support reporting and analytics requirements. Develop and maintain APDs (Analysis Process Designer) to extract data from BW and push output files to application servers for downstream consumption. Analyze, troubleshoot, and optimize BW query and load performance, particularly for large data volumes. Build and support connectivity between SAP BW and external data platforms, preferably Cloudera and/or Google Cloud Platform (GCP). Design, schedule, and monitor Process Chains to automate data loads and ensure data availability SLAs are met. Manage Transport Requests across development, quality, and production landscapes following change management best practices. Create and maintain technical documentation, including design specs, data flow diagrams, and process runbooks. Collaborate with functional consultants, business analysts, and downstream data teams to translate business requirements into technical solutions. Provide production support, root-cause analysis, and long-term fixes for data and performance issues Requ

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We are looking for a highly motivated Software Engineer in our Furnishing Platform team to build scalable systems and data pipelines to power our consumer credit reporting. You will partner closely with our Product, Compliance, Servicing, and Credit teams to design robust reporting systems. The systems you will work on are vital for delivering accurate and timely data from Affirm’s financial product portfolio to Consumer Reporting Agencies. Affirm is growing fast and we want you to enable us to scale our products to 10x and beyond through building world-class systems which enable Affirm in its mission to provide honest financial products which improve lives. We are only just getting started! Come join us as we build a beloved, lasting financial services brand predicated on honesty and trust. It’s going to be an amazing ride! What you’ll do With the support of your team’s tech lead and manager, you will break down larger projects into individual tasks, deliver them in multiple phases, and collaborate with others to ensure timely delivery of your work. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will contribute to a sense of community on your team by engaging in growth and development activities such as participation in the interview process. What we look for You have a total of 1.5+ years of experience as a software engineer. You have experience designing, deve

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We are looking for a highly motivated Software Engineer in our Furnishing Platform team to build scalable systems and data pipelines to power our consumer credit reporting. You will partner closely with our Product, Compliance, Servicing, and Credit teams to design robust reporting systems. The systems you will work on are vital for delivering accurate and timely data from Affirm’s financial product portfolio to Consumer Reporting Agencies. Affirm is growing fast and we want you to enable us to scale our products to 10x and beyond through building world-class systems which enable Affirm in its mission to provide honest financial products which improve lives. We are only just getting started! Come join us as we build a beloved, lasting financial services brand predicated on honesty and trust. It’s going to be an amazing ride! What you’ll do With the support of your team’s tech lead and manager, you will break down larger projects into individual tasks, deliver them in multiple phases, and collaborate with others to ensure timely delivery of your work. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will contribute to a sense of community on your team by engaging in growth and development activities such as participation in the interview process. On-Call Rotation - There would be an on-call rotation for this role as a requirement What we look for You have a tot

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the org. We are hiring an Analytics Engineer focused on maintaining and optimizing our finance data platform , improving reliability, efficiency, and performance of our pipelines and core datasets. This role is ideal for someone who enjoys operational ownership, building strong foundations, and making data systems easier and safer to run at scale. What You’ll Do Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases. Improve platform reliability through strong testing patterns, alerting, and runbooks. Own and document data pipelines and lineage, ensuring changes are understandable and auditable. Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes. Optimize performance and cost in Snowflake and dbt to support scaling needs. Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets. Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows). What We Look For 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems. Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation). Experience operating in a modern development workflow: Git and pull-request based collaboration (GitHub preferred). Familiarity with standard IDEs and collaborative debugging practices. E

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

About the Role We're looking for a driven, phone-first Sales Sourcer to help us build out our sales team. This isn't a passive recruiting role you'll be spending your days finding great sales talent on LinkedIn, picking up the phone, and convincing top candidates to take the conversation further. If you love the thrill of a cold call and get excited about finding the one great candidate out of a hundred profiles, this is for you. What You'll Do Source sales candidates directly on LinkedIn, reviewing large volumes of profiles to identify the right fit Conduct cold outreach via phone, text, and LinkedIn messages phone calls are your primary weapon Pitch our company compellingly and handle objections in real time Qualify candidates against a clear ideal profile before passing to the recruiting team Build and maintain organized candidate pipelines and track outreach activity Continuously refine your sourcing approach and identify the best target companies to recruit from What We're Looking For 1 year of experience in recruiting, sourcing, or sales we care more about your drive than your resume A genuine love for cold calling; you're comfortable picking up the phone and starting conversations from scratch Strong communication skills you can pitch a company clearly and confidently in under 90 seconds High attention to detail when evaluating candidate backgrounds; you can quickly assess quality from a LinkedIn profile Self-starter mentality you don't need to be told twice and you figure things out Passion for sales and an understanding of what makes a great sales rep Nice to Have Prior experience sourcing or recruiting for sales roles Familiarity with tools like LinkedIn Recruiter Background in sales or a sales environment Additional Job details The base salary range for this position is $90k - $100k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experien

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s mission is to bring the power of computing and software development to everyone. We are developing a powerful and extensible toolkit that our customers can leverage to solve a variety of different problems and workflows. We’ve seen our most sophisticated customers use the product to run global processes across thousands of employees, coordinate precision manufacturing pipelines, and consolidate previously siloed mission-critical data into a single source of truth. The complexity of these use cases requires us to be extremely thoughtful about how we design and implement new functionality in the product and make sure it’s both easy to use and comprehend for our customers and maintainable for us. As a Full-Stack, Backend engineer at Airtable, you will have the opportunity to work with customers to deeply understand their needs and workflows. You will collaborate with cross-functional partners across product management, design, research and data science to create innovative new features that enable our customers to do their best work. You will be responsible for owning and executing the end-to-end implementation of these new features that will contribute to making our toolkit even more powerful and successful. We currently have openings on: The Admin & Governance Team (Full-Stack/BE) ensures Airtable is secure, compliant, and enterprise-ready. It owns key admin capabilities like the Admin Panel, SSO, and audit systems, as well as foundational features like User Groups. This team's mission is to accelerate organizational value for the largest customers with enterprise-first governance and controls. The Omni Capability & Quality Team (Full-Stack/BE) brings the power of AI directly to Airtable end users—