Principal HANA Database Administrator

Senior Data Scientist 2

Senior Software Engineer 2 (Ruby on Rails) | Klara

Senior Software Engineer 2

IAD / SAD / LAD GCP Data Engineer

Associate Data Engineer

QE Specialist

C# Developer (SSE)

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Role Description: <ul><li>The Principal HANA Database Administrator will serve as the organization’s top technical authority for SAP HANA database environments.</li><li>This role is responsible for designing, implementing, and optimizing large-scale HANA systems to ensure high availability, security, and performance.</li><li>The individual will lead strategic initiatives, mentor team members, and collaborate with cross-functional teams to support mission-critical enterprise applications.</li></ul> Responsibilities: Architecture &amp; Strategy <ul><li>Define enterprise-level SAP HANA architecture and standards.</li><li>Develop strategies for scalability, high availability, disaster recovery, and security compliance.</li></ul> Database Administration <ul><li>Install, configure, and upgrade SAP HANA systems.</li><li>Perform advanced performance tuning, query optimization, and memory management.</li><li>Monitor system health and proactively resolve issues.</li></ul> Data Management <ul><li>Manage data provisioning, replication, and integration with SAP and non-SAP systems.</li><li>Ensure compliance with data governance and security standards.</li></ul> Leadership <ul><li>Act as a subject matter expert for SAP HANA across the organization.</li><li>Mentor junior DBAs and provide technical guidance to project teams.</li><li>Drive automation and best practices for database operations.</li></ul> Innovation <ul><li>Evaluate emerging technologies and recommend enhancements.</li><li>Lead initiatives to improve efficiency and reduce operational risk.</li></ul> Requirements: Education: <ul><li>Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.</li></ul> Experience: <ul><li>10+ years of database administration experience, with at least 5 years in SAP HANA.</li><li>Proven track record managing large-scale, mission-critical HANA environments.</li></ul> Technical Skills: <ul><li>Expertise in SAP HANA architecture, sizing, and performance tuning.</li><li>Strong knowledge of Linux OS, virtualization, and cloud platforms (AWS, Azure, GCP).</li><li>Familiarity with SAP Basis and integration with S/4HANA, BW/4HANA.</li></ul> Certifications: <ul><li>SAP Certified Technology Specialist – SAP HANA.</li><li>Additional certifications in cloud or database technologies preferred.</li></ul>

Responsibilities: <ul><li>Lead the design and development of LLM-powered solutions for clinical summarization, intelligent chat, and document understanding to improve patient care outcomes.</li><li>Architect and implement end-to-end machine learning pipelines, including Retrieval-Augmented Generation (RAG) systems using vector databases such as Pinecone and Weaviate.</li><li>Fine-tune and optimize state-of-the-art language models (e.g., GPT, LLaMA, Mistral) and apply advanced prompt engineering to address specialty-specific healthcare use cases.</li><li>Own project delivery end to end, collaborating with stakeholders to ensure AI solutions are ethical, scalable, reliable, and well-governed.</li><li>Mentor and support junior data scientists, fostering a culture of experimentation, learning, and innovation.</li></ul> Requirements: <ul><li>Experience: 8–12 years in Data Science/ML, with at least 3+ years specifically focused on LLMs and Generative AI.&nbsp;</li><li>Technical Mastery: Deep hands-on expertise in Python and frameworks like PyTorch, Hugging Face, LangChain, or LlamaIndex.&nbsp;</li><li>Cloud Fluency: Proven ability to deploy models at scale using AWS SageMaker, Azure ML, or GCP Vertex AI.&nbsp;</li><li>MLOps Mindset: Experience with MLflow, Airflow, Docker, and Kubernetes to ensure our "bold innovations" are also stable and reliable.&nbsp;</li><li>Academic Foundation: A strong grasp of statistical analysis and evaluation techniques to mitigate hallucinations and ensure clinical accuracy.&nbsp;</li></ul>

Responsibilities: <ul><li>Design, build, and maintain scalable backend systems using Ruby on Rails, ensuring reliability, performance, and an exceptional user experience.</li><li>Collaborate closely with Product and Design teams to translate customer needs into high-impact technical solutions, balancing simplicity with scalability.</li><li>Define and communicate clear technical specifications by breaking down complex requirements into actionable, well-structured implementation plans.</li><li>Uphold engineering excellence through test-driven development (TDD), comprehensive integration testing, and disciplined API design and management.</li><li>Optimize data storage and messaging systems, including PostgreSQL, NoSQL databases, and RabbitMQ, to ensure system efficiency and stability.</li><li>Mentor and support fellow engineers through pairing, knowledge sharing, and leading refactoring initiatives to continuously raise team-wide technical standards.</li></ul> Requirements: <ul><li>Technical Depth: A degree in Computer Science (or equivalent experience) and 3+ years of professional mastery in Ruby and its frameworks (Rails, Grape, or Sinatra).&nbsp;</li><li>A Quality Mindset: A strong TDD advocate who lives and breathes RSpec.&nbsp;</li><li>Systems Thinking: Deep experience with relational databases and message-driven architectures. You understand how parts of a system talk to one another.&nbsp;</li><li>Growth Mindset: A drive to learn and take ownership. You dont wait for permission to make things better.&nbsp;</li><li>Effective Communication: The ability to influence technical decisions and explain "the why" to both technical and non-technical stakeholders.</li></ul>

Responsibilities:&nbsp; <ul><li>Lead and own the architectural design of the cloud platform, ensuring solutions align with scalability requirements and long-term business objectives.</li><li>Define and execute the technical roadmap in collaboration with cross-functional stakeholders to advance the product vision.</li><li>Translate complex business requirements into clear technical specifications, actionable milestones, and high-quality deliverables.</li><li>Drive engineering excellence by proactively managing functional and non-functional requirements, and initiating corrective action when outcomes diverge from expectations.</li><li>Mentor and develop engineers through structured design, code, and operational reviews, fostering a culture of continuous improvement and technical rigor.</li></ul> Requirements: <ul><li>Experience: 10+ years of software development experience, with at least 3+ years in a technical leadership role.&nbsp;</li><li>Education: Bachelor’s or Master’s degree in Computer Science or a related field.&nbsp;</li><li>Deep Technical Expertise: Extensive mastery of Java, Spring Boot, and SQL.&nbsp;</li><li>Cloud &amp; Distributed Systems: Proven experience designing and operating modern cloud-native, fault-tolerant distributed services (preferably on AWS).&nbsp;</li><li>Architecture: Solid understanding of Microservices and REST API standards.&nbsp;</li><li>Quality Focus: Strong experience in writing Unit and API tests to ensure platform stability.&nbsp;</li><li>Soft Skills: Exceptional strategic thinking and the ability to communicate technical concepts to non-technical stakeholders.</li></ul>

Responsibilities: Architecture &amp; Design:&nbsp; <ul><li>Design end-to-end data architectures that integrate real-time streaming (Kafka, GCP Pub/sub) and batch processing (Big Query OR Databricks).</li></ul> Pipeline Development:&nbsp; <ul><li>Build and maintain robust ETL/ELT pipelines flowing into BigQuery/Databricks, ensuring data is clean, modeled, and ready for consumption.</li></ul> Custom Integration:&nbsp; <ul><li>Develop custom APIs and microservices using Java/Python/C# to facilitate data movement between niche systems and the data lakehouse.</li></ul> Infrastructure Management:&nbsp; <ul><li>Deploy and manage data workloads on Google Kubernetes Engine (GKE), ensuring high availability and cost-efficiency.</li></ul> Technical Leadership:&nbsp; <ul><li>Mentor junior engineers, conduct code reviews, and establish DataOps best practices (CI/CD, automated testing, and monitoring).</li></ul> Data Reliability:&nbsp; <ul><li>Implement data quality frameworks to ensure accuracy and lineage across the hybrid environment.</li></ul> Requirements: <ul><li>Experience with Terraform &amp; Azure Dev Ops (ADO).</li><li>Knowledge of workflow orchestrators like Apache Airflow (Cloud Composer).</li><li>Experience implementing Data Governance (metadata management, data cataloging).</li><li>Data Processing &amp; Storage</li><li>BigQuery: Expert-level SQL and experience with partition/cluster optimization.</li><li>Databricks: Deep knowledge of the Lakehouse architecture, Delta Lake, and Spark (PySpark/Scala) Software Engineering &amp; APIs</li><li>Languages: Proficiency in Java/Python/C# for backend development and custom data connectors.</li><li>API Design: Proven ability to build and consume RESTful APIs for data ingestion Streaming &amp; Infrastructure</li><li>Kafka/GCP Pub-Sub: Experience building event-driven architectures and managing producers/consumers.</li><li>GKE: Proficiency in containerization (Docker) and orchestrating data workloads on Kubernetes.</li></ul>

Responsibilities: <ul><li>Ability to troubleshoot problems in a live environment and provide real time help with critical issues.</li><li>Write code that is easily understood and maintainable by other team members.</li><li>Keep up to date with developments in technologies we are using.</li><li>Ability to communicate and work effectively, supporting various business departments.</li><li>Ability to work in fast-paced interdisciplinary environment.</li></ul> Requirements <ul><li>BA/BS in Computer Science or equivalent practical experience.&nbsp;</li><li>At least 3+ years of post-university experience as a full-stack engineer.</li><li>Solid knowledge of programming fundamentals—algorithms, data structures, design patterns, and paradigms.</li><li>Strong knowledge of Python.</li><li>Solid knowledge SQL and relational databases.</li><li>Knowledge of Extract-Transform-Load (ETL) and big data analytics tools.</li><li>Experience working in a cloud environment (AWS, Azure, GCP).</li><li>Familiarity with popular Python data analytics frameworks.</li><li>Familiarity with Snowflake or other large analytics engines.</li><li>Experience with data warehousing and working in environments with large scale, complex analytics requirements.</li><li>Familiarity with DAG-based job scheduling tools.</li><li>Cloud-native container orchestration platforms and tools.</li><li>Experience working in the Financial Services industry.</li></ul>

Responsibilities: <ul><li>Provide real-time QA oversight on the production floor, in warehouse areas, and during qualification activities.</li><li>Perform batch record and logbook review, ensuring accuracy, completeness, and compliance with GDP standards.</li><li>Execute and document line clearance and room readiness inspections prior to manufacturing activities.</li><li>Review qualification and validation protocols for clarity, compliance, and alignment with regulatory and internal quality expectations.</li><li>Support execution of qualification protocols by providing on-site quality presence during testing and ensuring deviations are properly documented and escalated. 6.	Initiate, investigate, and support closure of deviations, non-conformances, and CAPAs related to manufacturing and qualification activities.</li><li>Collaborate with cross-functional teams to ensure timely and compliant execution of commissioning, qualification, and validation activities.</li><li>Support the development and maintenance of site-specific quality procedures (SOPs, work instructions, forms) governing manufacturing, warehousing, engineering, maintenance, and validation operations.</li><li>Review and approve site procedures to ensure clarity and compliance with cGMP standards.</li><li>Maintain awareness of site policies, cGMP regulations, and evolving regulatory expectations applicable to sterile injectable operations.</li><li>Participate in internal walkthroughs, audit preparations, and readiness activities for regulatory inspections.</li><li>Support the implementation of continuous improvement initiatives and site quality metrics.</li></ul> Requirements: Qualifications/Experience <ul><li>Bachelor’s degree in a scientific, engineering, or technical discipline (e.g., Biology, Chemistry, Pharmacy, Engineering)</li><li>2–5 years of experience in quality assurance, manufacturing, or validation in a cGMP-regulated pharmaceutical or biotech manufacturing environment</li><li>Working knowledge of FDA, EU, and ICH guidelines related to sterile manufacturing, validation, and data integrity</li><li>Experience supporting commissioning and qualification activities is strongly preferred</li><li>Familiarity with GDP, batch record review, and deviation documentation processes</li></ul> Skills/Competencies <ul><li>Strong attention to detail and commitment to compliance</li><li>Solid written and verbal communication skills</li><li>Ability to work collaboratively across departments in a fast-paced environment</li><li>Comfortable supporting shop-floor activities and cross-functional execution teams</li><li>Proficient in using quality systems and document management tools</li><li>Flexible and adaptable to changing priorities and evolving project timelines</li><li>Commitment to data integrity, continuous improvement, and patient safety</li></ul>

Responsibilities: <ul><li>Develop distributed system architecture and system integration&nbsp;&nbsp;</li><li>Design event-driven applications leveraging microservices architecture on cloud platform&nbsp;</li><li>Carry out Model and assess complex IT solutions&nbsp;&nbsp;</li><li>Work closely with platform engineers and other IT professionals to choose compatible design solutions&nbsp;</li><li>Manage and comply with release management process&nbsp;</li><li>Analyze the scope and expected organizational impact of information systems&nbsp;</li><li>Evaluate existing systems and provide advice on how to meet organizational requirements&nbsp;</li><li>Ensure that the technical components of the project are in sync with the business needs of the organization&nbsp;</li><li>Ensure that information systems are secure from threat&nbsp;</li><li>Provide advice on project design, project costs, and expected benefit&nbsp;</li><li>Identifies technical debt and proactively recommends alternatives or improvements&nbsp;</li></ul> Requirements: <ul><li>University degree in Computer Science, Computer Engineering or related subjects preferred&nbsp;&nbsp;</li><li>8+ years of work experience building applications&nbsp;</li><li>Advanced understanding of IT infrastructure and enterprise architectures&nbsp;</li><li>Proven experience with microservices-based architecture&nbsp;</li><li>Proficiency in coding with modern programming languages such as C#, Python, or Node.js&nbsp;</li><li>API-first development experience&nbsp;</li><li>Experience with Cloud Computing (Azure preferable)&nbsp;</li><li>Extensive expertise in any modern document-oriented database, with a preference for MongoDB&nbsp;</li><li>Experience in developing components for Event-Driven Architecture, with a minimum of production-level experience using Event Hubs or Event Grid (or similar technologies like Kafka)&nbsp;</li><li>Experience working in an agile environment with a focus on engineering practices like testing, continuous integration, etc.&nbsp;</li><li>Good knowledge of virtualization&nbsp;&nbsp;</li><li>Analytics mindset with critical thinking and problem-solving skills&nbsp;</li><li>Fine knowledge of industry trends and emerging technologies&nbsp;</li><li>Fluent in English&nbsp;</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Dashboard Design and Development: Design, develop, and maintain interactive and user-friendly dashboards in PowerBI and Looker, focusing on clarity, performance, and data accuracy.&nbsp;</li><li>Data Lake Integration: Connect to and leverage data from various data lake sources on GCP, ensuring seamless data flow for visualization purposes.&nbsp;</li><li>Semantic Model Development: Develop and maintain robust semantic models in Looker (LookML) and PowerBI, ensuring data consistency, accuracy, and ease of use for reporting and analysis. This includes defining dimensions, measures, relationships, and calculations.&nbsp;</li><li>Machine Learning and GenAI Visualization: Create compelling visualizations to effectively communicate the results, performance, and insights derived from machine learning models and GenAI applications. This may involve visualizing model predictions, feature importance, natural language processing outputs, and other relevant data.&nbsp;</li><li>GCP Expertise: Utilize your strong understanding of GCP services to access, process, and prepare data for visualization. This may involve working with services such as BigQuery, Cloud Storage, and potentially data engineering pipelines built on GCP.&nbsp;</li><li>Collaboration: Partner closely with data scientists, data engineers, product managers, and business stakeholders to understand their data visualization needs and translate them into effective visual solutions.&nbsp;</li><li>Requirements Gathering: Elicit and document visualization requirements from various stakeholders, ensuring alignment with business objectives.&nbsp;</li><li>Performance Optimization: Optimize dashboard and visualization performance to ensure fast load times and efficient data rendering.&nbsp;</li><li>Data Quality Assurance: Ensure the accuracy, consistency, and reliability of data presented in visualizations.&nbsp;</li><li>Best Practices and Standards: Establish and enforce data visualization best practices and standards across the organization.&nbsp;</li><li>Training and Support: Provide guidance and support to other team members on data visualization tools and techniques.&nbsp;</li><li>Continuous Learning: Stay up to date with the latest trends and advancements in data visualization, PowerBI, Looker, GCP, and related technologies, particularly in the context of AI/ML.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s or master’s degree in computer science, Data Science, Statistics, Information Systems, or a related field.&nbsp;</li><li>Minimum of 3 years of experience as a Visualization Expert, Data Visualization Engineer, or a similar role.&nbsp;</li><li>Proven expertise in designing and developing interactive dashboards and reports using PowerBI and Looker.&nbsp;</li><li>Strong experience in connecting to and working with data lakes, preferably on the Google Cloud Platform (GCP).&nbsp;</li><li>Solid understanding and hands-on experience in developing semantic models, particularly with LookML in Looker and data modeling within PowerBI.&nbsp;</li><li>Preferable experience in creating visualizations specifically for machine learning and GenAI applications, understanding the nuances of presenting model outputs and insights.&nbsp;</li><li>Proficiency in SQL for data extraction and manipulation.&nbsp;</li><li>Familiarity with data warehousing concepts and data modeling techniques.&nbsp;</li><li>Experience with data preparation, ELT (preferred) / ETL processes.&nbsp;</li><li>Strong analytical and problem-solving skills with the ability to interpret complex data.&nbsp;</li><li>Excellent communication and presentation skills, with the ability to convey technical information to both technical and non-technical audiences.&nbsp;&nbsp;</li><li>Ability to work independently and collaboratively in a fast-paced environment.&nbsp;&nbsp;</li><li>Strong portfolio showcasing your data visualization skills and experience.&nbsp;</li></ul>

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31 gcp api Jobs found

Principal HANA Database Administrator

Senior Data Scientist 2

Senior Software Engineer 2 (Ruby on Rails) | Klara

Senior Software Engineer 2

IAD / SAD / LAD GCP Data Engineer

Associate Data Engineer

QE Specialist

C# Developer (SSE)

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

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31 gcp api Jobs found

Principal HANA Database Administrator

Senior Data Scientist 2

Senior Software Engineer 2 (Ruby on Rails) | Klara

Senior Software Engineer 2

IAD / SAD / LAD GCP Data Engineer

Associate Data Engineer

QE Specialist

C# Developer (SSE)

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

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