Principal HANA Database Administrator

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

Senior Business Intelligence Analyst

Associate Data Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Lead AI Engineer

DevSecOps Engineer

Lead DevSecOps Engineer

system engineer

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: 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>

Role Description: <ul><li>The Continuous Improvement EMIA team reports to Operations Automotive EMIA.</li><li>By providing new generation digital solutions to our Operational teams across EMIA, our team creates full transparency and speed in the ongoing digital &amp; lean transformation(s), which will enable all involved functions to leverage data to develop business insights and roadmap updates based upon clearly arranged and understandable data. Due to the extended scope, focusing also on the connecting processes from Supplier(s) to Manufacturing ending at the Customer(s) (internal and external) we will function as ‘the’ differentiator for our Company.</li><li>The Data Scientist Automotive EMIA will report to the Smart Factory Leader Automotive EMIA.&nbsp;</li></ul> Responsibilities:&nbsp; <ul><li>Lead projects and work together with our Automotive EMIA Operations plants, internal (IT, , Corporate Technology, CoE, SC, ..) and external partners in the area of Smart Factory (Applications, ML, AI, DL), aligned with Operations Automotive EMIA Strategy.</li><li>Lead Smart Factory improvement projects (Enhancements) of existing applications together with internal / external supplier and customers (project management) until the level of RTD (Ready To Deploy)</li><li>·Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems.</li><li>Identify and interpret data sources, manage large amounts of data, merge data sources together, ensure consistency of datasets, create visualizations to aid in understanding data.</li><li>Develop, Validate and Deploy (including Training and Coaching of the users) until the level of RTD (Ready To Deploy), Digital Factory Applications, ML models, contributing to waste elimination and efficiency improvements within all Operations functions (Manufacturing, Quality, SC, LOG, ….), this together with our internal and external partners.</li></ul>&nbsp;Requirements: Desired candidate &amp; Qualification <ul><li>Good understanding of a technology driven manufacturing company.</li><li>Knowledge of the core manufacturing technologies: Stamping, Plating, Assembly, Molding.</li><li>Experienced with data visualization tools like PowerBi, Tableau, ThingWorx,..</li><li>Good applied statistics skills, such as distributions, statistical testing, regression, etc.</li><li>Development experience in programming languages R, Python.</li><li>Knowledge, experience in JAVA scripting</li><li>Excellent pattern recognition and predictive modelling skills.</li><li>Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, neural networks and deep learning etc.</li><li>Experience in technologies like, Jupyter Notebooks, Numpy, Pandas, Seaborn, Scikit-learn, PyTorch and TensorFlow.</li><li>Exposure to recent developments in Deep Learning, Gen AI, Agentic AI domain.</li><li>Database skills, on-premises and cloud based.</li><li>Experience in AWS is an advantage, functional knowledge of AWS platforms such as Sagemaker, S3, and RedShift.</li><li>Excellent presentation skills in both spoken en written English.</li><li>&nbsp;Excellent and strong communicator</li><li>The ability to translate, explain and bring, complex data science topics to an easy understandable level, speeding up acceptance level in general.</li><li>Bachelor or master’s in data science</li><li>Team player with a solution focused problem-solving mentality.</li><li>Change agent with high Execution level, including training and coaching talents.</li><li>Passioned about the combination of Technology, Data, Analytics and Statistics with link to Quality, Product and Process Engineering</li><li>Inspired by and searching actively for new technologies and methods.</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>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>Oversee the design, development, and deployment of AI models and intelligent agents.</li><li>Ensure engineering best practices in model development, testing, and deployment.</li><li>Collaborate with IT and data teams to ensure scalable and secure integration of AI solutions.</li><li>Work closely with business and technical stakeholders to understand requirements and deliver impactful AI solutions.</li><li>Communicate effectively with global teams, bridging technical and business perspectives.</li><li>Support change management and adoption of AI tools across business units.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools.</li><li>Lead the design and development of solutions using Agentic AI&nbsp;</li></ul> Requirements: Basic Qualifications:<ul><li>10+ years of experience in software engineering, data science, AI, or a related field.</li><li>2+ years of experience in leadership role managing technical teams.</li><li>Proficiency in software development and statistical analysis.</li><li>Experience with Large Language Models and their applications.</li><li>Strong communication skills and the ability to present technical results to business stakeholders.</li><li>Experience with solution architecting and design.</li><li>Hands-on experience with cloud platforms such as Azure and/or AWS. </li><li>Proficiency in programming languages such as Python, R, or similar.</li><li>Bachelor’s or master’s in computer science, Mathematics, Statistics, or a related field.</li></ul> Preferred Qualifications:<ul><li>Experience working in a global enterprise or matrixed organization.</li><li>Familiarity with cloud platforms (Azure, AWS, GCP) and MLOps tools.</li><li>Experience with large language models and supporting workflows.</li><li>History of project leadership and development.</li><li>Experience in applications to sales, marketing, and market research&nbsp;</li></ul>

Responsibilities: <ul><li>﻿Support and maintain Kubernetes environments.</li><li>Design, implement, and maintain the infrastructure and deployment pipelines to support the development and deployment of our applications. </li><li>Collaborate with software engineers, system administrators, and other team members to identify and implement efficient and reliable solutions. </li><li>Automate processes and tasks to improve efficiency and scalability. </li><li>Provide technical support and assistance to the development team. </li><li>Monitor, analyze, and optimize system performance, ensuring high availability, scalability, and security. </li><li>Timely respond to incidents. </li><li>Maintain and enhance the security of our infrastructure, applications, and systems, ensuring compliance with industry best practices and regulatory requirements. </li><li>Provide On-call Weekly/Weekend off-hour L3-4 support on a rotational schedule with other team members.</li></ul> Requirements: <ul><li>6+ years of hands-on experience in DevSecOps or a similar role.</li><li>Strong knowledge of cloud platforms such as Azure and GCP and their security features.</li><li>Strong knowledge of SDLC, CI/CD pipelines, and infrastructure automation.</li><li>Strong knowledge of CI/CD tools such as Azure DevOps or an equivalent.</li><li>Confident knowledge of IaC approach, testing techniques and strong hands-on experience with infrastructure management tools such as Terraform.</li><li>Good understanding of Configuration Management and hands-on experience with CM tools such as Ansible.</li><li>Strong understanding of networking concepts, including the OSI model (protocols, etc.).</li><li>Expertise in system administration for both Linux and Windows environments.</li><li>Ability to comprehend the objectives of a task, propose and advocate for solutions, and successfully implement them.</li></ul>

Responsibilities: <ul><li>Contribute to Infrastructure as a Code</li><li>Support and maintain Kubernetes environments</li><li>Design, implement, and maintain the infrastructure and deployment pipelines to support the development and deployment of our applications.</li><li>Collaborate with software engineers, system administrators, and other team members to identify and implement efficient and reliable solutions.</li><li>Automate processes and tasks to improve efficiency and scalability.</li><li>Provide technical support and assistance to the development team.</li><li>Monitor, analyze, and optimize system performance, ensuring high availability, scalability, and security.</li><li>Timely respond to incidents.</li><li>Maintain and enhance the security of our infrastructure, applications, and systems, ensuring compliance with industry best practices and regulatory&nbsp;</li><li>requirements.</li><li>Provide On-call Weekly/Weekend off-hour L3-4 support on a rotational schedule with other team members</li><li>Develop and maintain system documentation</li><li>Stay up-to-date with the latest trends, technologies, and best practices in DevSecOps and cybersecurity</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, Information Security, or a related field.</li><li>6+ years of hands-on experience in DevSecOps or a similar role. (8+ years total)</li><li>Strong knowledge of cloud platforms such as Azure and GCP and their security features.</li><li>Strong knowledge of SDLC, CI/CD pipelines, and infrastructure automation.</li><li>Strong knowledge of CI/CD tools such as Azure DevOps or an equivalent.</li><li>Confident knowledge of containerization technologies and strong hands-on experience with Docker and Kubernetes.</li><li>Confident knowledge of IaC approach, testing techniques and strong handson experience with infrastructure management tools such as Terraform.</li><li>Good understanding of modern monitoring tools and practice</li></ul>

Responsibilities: <ul><li>Provide application L1/L2 support and system checks (CPU, disk usage, logs, services)</li><li>Troubleshoot and resolve system and application issues, and provide on-site technical support to ensure timely resolution and minimal disruption to business operations</li><li>Monitor application health and system alerts, escalating issues as needed</li><li>Log incidents and service requests in the ticketing system, ensuring timely resolution</li><li>Coordinate with L3 teams and vendors for issue escalation and follow-up</li><li>Perform routine maintenance tasks, such as application updates, patching, and backups</li><li>Maintain clear documentation of issues, fixes, and procedures</li><li>Participate in system testing, deployment, and post-deployment support activities</li><li>Assist in user access management and configuration </li><li>Requirements:</li><li>Diploma/Degree in Electrical Engineering, Computer Science, Communications Engineering or equivalent</li><li>Minimum 2 years in application maintenance, support or server infrastructure setup</li><li>Experience participating in Kubernetes cluster projects, with proficiency in using relevant commands to check application logs</li><li>Experience with at least two of the following Virtualization Technology/Platforms: VMware, Xen, KVM, OpenStack, Cloud Stack, Azure Stack</li><li>Experience with cloud orchestration, configuration management and auto-scaling techniques</li><li>Thorough knowledge of networking, routers, switches, and WiFi setup</li><li>Hands on experience in deploying ceph using different file system such as object storage, rbd, cephfs storage</li><li>Good knowledge of storage technologies, such as NAS, SAN, SDS</li><li>Experience with automation tools such as Salt/Chef/Puppet/Ansible</li><li>Experience with load balancing setup for TCP/IP, HTTP, DNS, routings.</li><li>Experience in using software version control</li><li>Knowledge of IT security standards, for instance from CIS or IM8.</li><li>Experience in IT security policy management and enforcing IT security</li><li>Knowledge of computer hardware components and ability to restore faulty servers to working condition.</li><li>Experience in coding or scripting languages such as bash, windows batch script, powershell, perl, python, etc.&nbsp;</li></ul>

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17 azure deveops Jobs found

Principal HANA Database Administrator

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

Senior Business Intelligence Analyst

Associate Data Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Lead AI Engineer

DevSecOps Engineer

Lead DevSecOps Engineer

system engineer

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17 azure deveops Jobs found

Principal HANA Database Administrator

Senior Data Scientist 2

IAD / SAD / LAD GCP Data Engineer

Senior Business Intelligence Analyst

Associate Data Engineer

Senior Machine Learning Engineer (Production & MLOps Focus)

Lead AI Engineer

DevSecOps Engineer

Lead DevSecOps Engineer

system engineer

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