38 Sparql Jobs - Page 2

Lead Knowledge Engineer Hyderabad, India Data Management 311636 Job Description About The Role: Grade Level (for internal use): 11 The Role : The Knowledge Engineering team are seeking a Lead Knowledge Engineer to support our strategic transformation from a traditional data organization into a next generation interconnected data intelligence organization. The Team : The Knowledge Engineering team within data strategy and governance helps to lead fundamental organizational and operational change driving our linked data, open data, and data governance strategy, both internally and externally. The team partners closely with data and software engineering to envision and build the next generation of data architecture and tooling with modern technologies. The Impact : Knowledge Engineering efforts occur within the broader context of major strategic initiatives to extend market leadership and build next-generation data, insights and analytics products that are powered by our world class datasets. What’s in it for you : The Lead Knowledge Engineer role is an opportunity to work as an individual contributor in creatively solving complex challenges alongside visionary leadership and colleagues. It’s a role with highly visible initiatives and outsized impact. The wider division has a great culture of innovation, collaboration, and flexibility with a focus on delivery. Every person is respected and encouraged to be their authentic self. Responsibilities : Develop, implement, and continue to enhance ontologies, taxonomies, knowledge graphs, and related semantic artefacts for interconnected data, as well as topical/indexed query, search, and asset discovery Design and prototype data / software engineering solutions enabling to scale the construction, maintenance and consumption of semantic artefacts and interconnected data layer for various application contexts Provide thought leadership for strategic projects ensuring timelines are feasible, work is effectively prioritized, and deliverables met Influence the strategic semantic vision, roadmap, and next-generation architecture Execute on the interconnected data vision by creating linked metadata schemes to harmonize semantics across systems and domains Analyze and implement knowledge organization strategies using tools capable of metadata management, ontology management, and semantic enrichment Influence and participate in governance bodies to advocate for the use of established semantics and knowledge-based tools Qualifications: Able to communicate complex technical strategies and concepts in a relatable way to both technical and non-technical stakeholders and executives to effectively persuade and influence 5+ years of experience with ontology development, semantic web technologies (RDF, RDFS, OWL, SPARQL) and open-source or commercial semantic tools (e.g., VocBench, TopQuadrant, PoolParty, RDFLib, triple stores); Advanced studies in computer science, knowledge engineering, information sciences, or related discipline preferred 3+ years of experience in advanced data integration with semantic and knowledge graph technologies in complex, enterprise-class, multi-system environment(s); skilled in all phases from conceptualization to optimization Programming skills in a mainstream programming language (Python, Java, JavaScript), with experience in utilizing cloud services (AWS, Google Cloud, Azure) is a great bonus Understanding of the agile development life cycle and the broader data management discipline (data governance, data quality, metadata management, reference and master data management) S&P Global Enterprise Data Organization is a unified, cross-divisional team focused on transforming S&P Global’s data assets. We streamline processes and enhance collaboration by integrating diverse datasets with advanced technologies, ensuring efficient data governance and management. About S&P Global Commodity Insights At S&P Global Commodity Insights, our complete view of global energy and commodities markets enables our customers to make decisions with conviction and create long-term, sustainable value. We’re a trusted connector that brings together thought leaders, market participants, governments, and regulators to co-create solutions that lead to progress. Vital to navigating Energy Transition, S&P Global Commodity Insights’ coverage includes oil and gas, power, chemicals, metals, agriculture and shipping. S&P Global Commodity Insights is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today. For more information, visit http://www.spglobal.com/commodity-insights. What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. - Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf - 10 - Officials or Managers (EEO-2 Job Categories-United States of America), DTMGOP103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 311636 Posted On: 2025-05-14 Location: Hyderabad, Telangana, India

Sr Semantic Engineer – Research Data and Analytics What you will do Let’s do this. Let’s change the world. In this vital role you will be part of Research’s Semantic Graph Team is seeking a dedicated and skilled Semantic Data Engineer to build and optimize knowledge graph-based software and data resources. This role primarily focuses on working with technologies such as RDF, SPARQL, and Python. In addition, the position involves semantic data integration and cloud-based data engineering. The ideal candidate should possess experience in the pharmaceutical or biotech industry, demonstrate deep technical skills, and be proficient with big data technologies and demonstrate experience in semantic modeling. A deep understanding of data architecture and ETL processes is also essential for this role. In this role, you will be responsible for constructing semantic data pipelines, integrating both relational and graph-based data sources, ensuring seamless data interoperability, and leveraging cloud platforms to scale data solutions effectively. Roles & Responsibilities: Develop and maintain semantic data pipelines using Python, RDF, SPARQL, and linked data technologies. Develop and maintain semantic data models for biopharma scientific data Integrate relational databases (SQL, PostgreSQL, MySQL, Oracle, etc.) with semantic frameworks. Ensure interoperability across federated data sources, linking relational and graph-based data. Implement and optimize CI/CD pipelines using GitLab and AWS. Leverage cloud services (AWS Lambda, S3, Databricks, etc.) to support scalable knowledge graph solutions. Collaborate with global multi-functional teams, including research scientists, Data Architects, Business SMEs, Software Engineers, and Data Scientists to understand data requirements, design solutions, and develop end-to-end data pipelines to meet fast-paced business needs across geographic regions. Collaborate with data scientists, engineers, and domain experts to improve research data accessibility. Adhere to standard processes for coding, testing, and designing reusable code/components. Explore new tools and technologies to improve ETL platform performance. Participate in sprint planning meetings and provide estimations on technical implementation. Maintain comprehensive documentation of processes, systems, and solutions. Harmonize research data to appropriate taxonomies, ontologies, and controlled vocabularies for context and reference knowledge. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications and Experience: Doctorate Degree OR Master’s degree with 4 - 6 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Bachelor’s degree with 6 - 8 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field OR Diploma with 10 - 12 years of experience in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field Preferred Qualifications and Experience: 6+ years of experience in designing and supporting biopharma scientific research data analytics (software platforms) Functional Skills: Must-Have Skills: Advanced Semantic and Relational Data Skills: Proficiency in Python, RDF, SPARQL, Graph Databases (e.g. Allegrograph), SQL, relational databases, ETL pipelines, big data technologies (e.g. Databricks), semantic data standards (OWL, W3C, FAIR principles), ontology development and semantic modeling practices. Cloud and Automation ExpertiseGood experience in using cloud platforms (preferably AWS) for data engineering, along with Python for automation, data federation techniques, and model-driven architecture for scalable solutions. Technical Problem-SolvingExcellent problem-solving skills with hands-on experience in test automation frameworks (pytest), scripting tasks, and handling large, complex datasets. Good-to-Have Skills: Experience in biotech/drug discovery data engineering Experience applying knowledge graphs, taxonomy and ontology concepts in life sciences and chemistry domains Experience with graph databases (Allegrograph, Neo4j, GraphDB, Amazon Neptune) Familiarity with Cypher, GraphQL, or other graph query languages Experience with big data tools (e.g. Databricks) Experience in biomedical or life sciences research data management Soft Skills: Excellent critical-thinking and problem-solving skills Good communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Associate Data Engineer Graph – Research Data and Analytics What you will do Let’s do this. Let’s change the world. In this vital role you will be part of Research’s Semantic Graph. Team is seeking a dedicated and skilled Data Engineer to design, build and maintain solutions for scientific data that drive business decisions for Research. You will build scalable and high-performance, graph-based, data engineering solutions for large scientific datasets and collaborate with Research partners. The ideal candidate possesses experience in the pharmaceutical or biotech industry, demonstrates deep technical skills, has experience with semantic data modeling and graph databases, and understands data architecture and ETL processes. Roles & Responsibilities: Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions Contribute to data pipeline projects from inception to deployment, manage scope, timelines, and risks Contribute to data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency Optimize large datasets for query performance Collaborate with global multi-functional teams including research scientists to understand data requirements and design solutions that meet business needs Implement data security and privacy measures to protect sensitive data Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions Collaborate with Data Architects, Business SMEs, Software Engineers and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions Identify and resolve data-related challenges Adhere to best practices for coding, testing, and designing reusable code/component Explore new tools and technologies that will help to improve ETL platform performance Participate in sprint planning meetings and provide estimations on technical implementation Maintain documentation of processes, systems, and solutions What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications and Experience: Bachelor’s degree and 1to 3 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience OR Diploma and 4 to 7 years of Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics or related field experience Functional Skills: Must-Have Skills: Advanced Semantic and Relational Data Skills: Proficiency in Python, RDF, SPARQL, Graph Databases (e.g. Allegrograph), SQL, relational databases, ETL pipelines, big data technologies (e.g. Databricks), semantic data standards (OWL, W3C, FAIR principles), ontology development and semantic modeling practices. Hands on experience with big data technologies and platforms, such as Databricks, workflow orchestration, performance tuning on data processing. Excellent problem-solving skills and the ability to work with large, complex datasets Good-to-Have Skills: A passion for tackling complex challenges in drug discovery with technology and data Experience with system administration skills, such as managing Linux and Windows servers, configuring network infrastructure, and automating tasks with shell scripting. Examples include setting up and maintaining virtual machines, troubleshooting server issues, and ensuring data security through regular updates and backups. Solid understanding of data modeling, data warehousing, and data integration concepts Solid experience using RDBMS (e.g. Oracle, MySQL, SQL server, PostgreSQL) Knowledge of cloud data platforms (AWS preferred) Experience with data visualization tools (e.g. Dash, Plotly, Spotfire) Experience with diagramming and collaboration tools such as Miro, Lucidchart or similar tools for process mapping and brainstorming Experience writing and maintaining user documentation in Confluence Professional Certifications: Databricks Certified Data Engineer Professional preferred Soft Skills: Excellent critical-thinking and problem-solving skills Good communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description We are seeking a Reference Data Management Senior Analyst who a s the Reference Data Product team member of the Enterprise Data Management organization, will be responsible for managing and promoting the use of reference data, partnering with business Subject Mater Experts on creation of vocabularies / taxonomies and ontologies, and developing analytic solutions using semantic technologies . Roles & Responsibilities Work with Reference Data Product Owner, external resources and other engineers as part of the product team? ? Develop and maintain semantically appropriate concepts ? ? Identify and address conceptual gaps in both content and taxonomy ? Maintain ontology source vocabularies for new or edited codes? ? Support product teams to help them leverage taxonomic solutions ? Analyze the data from public/internal datasets. ? Develop a Data Model/schema for taxonomy. ? Create a taxonomy in Semaphore Ontology Editor. ? Perform Bulk-import data templates into Semaphore to add/update terms in taxonomies. ? Prepare SPARQL queries to generate adhoc reports. ? Perform Gap Analysis on current and updated data? ? Maintain taxonomies in Semaphore through Change Management process. ? Develop and optimize automated data ingestion / pipelines through Python/ PySpark when APIs are available ? Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs ? Identify and resolve complex data-related challenges ? Participate in sprint planning meetings and provide estimations on technical implementation . Basic Qualifications and Experience Master’s degree with 6 years of experience in Business, Engineering, IT or related field OR Bachelor’s degree with 8 years of experience in Business, Engineering, IT or related field OR Diploma with 9+ years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: Knowledge of controlled vocabularies, classification, ontology and taxonomy? ? Experience in ontology development using Semaphore, or a similar tool? ? Hands on experience writing SPARQL queries on graph data ? Excellent problem-solving skills and the ability to work with large, complex datasets ? Understanding of data modeling, data warehousing, and data integration concepts Good-to-Have Skills: Hands on experience writing SQL using any RDBMS (Redshift, Postgres, MySQL, Teradata, Oracle, etc.). ? Experience using cloud services such as AWS or Azure or GCP? ? Experience working in Product Teams environment ? Knowledge of Python/R, Databricks, cloud data platforms ? Knowledge of NLP (Natural Language Processing) and AI (Artificial Intelligence) for extracting and standardizing controlled vocabularies. ? Strong understanding of data governance frameworks, tools, and best practices ? Professional Certifications Databricks Certificate preferred? SAFe ® Practitioner Certificate preferred? Any Data Analysis certification (SQL , Python ) Any cloud certification (AWS or AZURE) Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Project Role : Application Architect Project Role Description : Provide functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Must have skills : Manufacturing Operations Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : BTech BE Job Title:Industrial Data Architect Summary :We are seeking a highly skilled and experienced Industrial Data Architect with a proven track record in providing functional and/or technical expertise to plan, analyse, define and support the delivery of future functional and technical capabilities for an application or group of applications. Well versed with OT data quality, Data modelling, data governance, data contextualization, database design, and data warehousing. Must have Skills:Domain knowledge in areas of Manufacturing IT OT in one or more of the following verticals Automotive, Discrete Manufacturing, Consumer Packaged Goods, Life ScienceKey Responsibilities: Industrial Data Architect will be responsible for developing and overseeing the industrial data architecture strategies to support advanced data analytics, business intelligence, and machine learning initiatives. This role involves collaborating with various teams to design and implement efficient, scalable, and secure data solutions for industrial operations. Focused on designing, building, and managing the data architecture of industrial systems. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Own the offerings and assets on key components of data supply chain, data governance, curation, data quality and master data management, data integration, data replication, data virtualization. Create scalable and secure data structures, integrating with existing systems and ensuring efficient data flow. Qualifications: Data Modeling and Architecture:oProficiency in data modeling techniques (conceptual, logical, and physical models).oKnowledge of database design principles and normalization.oExperience with data architecture frameworks and methodologies (e.g., TOGAF). Database Technologies:oRelational Databases:Expertise in SQL databases such as MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.oNoSQL Databases:Experience with at least one of the NoSQL databases like MongoDB, Cassandra, and Couchbase for handling unstructured data.oGraph Databases:Proficiency with at least one of the graph databases such as Neo4j, Amazon Neptune, or ArangoDB. Understanding of graph data models, including property graphs and RDF (Resource Description Framework).oQuery Languages:Experience with at least one of the query languages like Cypher (Neo4j), SPARQL (RDF), or Gremlin (Apache TinkerPop). Familiarity with ontologies, RDF Schema, and OWL (Web Ontology Language). Exposure to semantic web technologies and standards. Data Integration and ETL (Extract, Transform, Load):oProficiency in ETL tools and processes (e.g., Talend, Informatica, Apache NiFi).oExperience with data integration tools and techniques to consolidate data from various sources. IoT and Industrial Data Systems:oFamiliarity with Industrial Internet of Things (IIoT) platforms and protocols (e.g., MQTT, OPC UA).oExperience with either of IoT data platforms like AWS IoT, Azure IoT Hub, and Google Cloud IoT Core.oExperience working with one or more of Streaming data platforms like Apache Kafka, Amazon Kinesis, Apache FlinkoAbility to design and implement real-time data pipelines. Familiarity with processing frameworks such as Apache Storm, Spark Streaming, or Google Cloud Dataflow.oUnderstanding of event-driven design patterns and practices. Experience with message brokers like RabbitMQ or ActiveMQ.oExposure to the edge computing platforms like AWS IoT Greengrass or Azure IoT Edge AI/ML, GenAI:oExperience working on data readiness for feeding into AI/ML/GenAI applicationsoExposure to machine learning frameworks such as TensorFlow, PyTorch, or Keras. Cloud Platforms:oExperience with cloud data services from at least one of the providers like AWS (Amazon Redshift, AWS Glue), Microsoft Azure (Azure SQL Database, Azure Data Factory), and Google Cloud Platform (BigQuery, Dataflow). Data Warehousing and BI Tools:oExpertise in data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google BigQuery).oProficiency with Business Intelligence (BI) tools such as Tableau, Power BI, and QlikView. Data Governance and Security:oUnderstanding of data governance principles, data quality management, and metadata management.oKnowledge of data security best practices, compliance standards (e.g., GDPR, HIPAA), and data masking techniques. Big Data Technologies:oExperience in big data platforms and tools such as Hadoop, Spark, and Apache Kafka.oUnderstanding of distributed computing and data processing frameworks. Excellent Communication:Superior written and verbal communication skills, with the ability to effectively articulate complex technical concepts to diverse audiences. Problem-Solving Acumen:A passion for tackling intricate challenges and devising elegant solutions. Collaborative Spirit:A track record of successful collaboration with cross-functional teams and stakeholders. Certifications:AWS Certified Data Engineer Associate / Microsoft Certified:Azure Data Engineer Associate / Google Cloud Certified Professional Data Engineer certification is mandatory Minimum of 14-18 years progressive information technology experience. Qualifications BTech BE

We are looking for S enior Ontology Engineer - Semantic Data Modelling . BUSINESS AREA: Siemens Energy business - Partner & driver of energy transition. Building innovative technologies, extensive energy experience and an ambitious strategy to decarbonize global energy systems are all central to our efforts to be the partner and driver of the energy transition. Technology advances every day. Information Technology is crucial to our future. As part of our IT R & D team, youll build extensive IT digital systems, develop plans for using cloud technologies, and create industrial data analytics platforms. Your work will benefit everyone at Siemens business entities. If you are determined to take us further with innovative IT solutions that keep our world connected and businesses moving forward, then theres a place for you at Siemens Energy. Join our Digitalization Technology and Services (DTS) team based in Bangalore. WHAT DIGITAL SOLUTIONS/PLATFORMS WE ARE BUILDING: Knowledge Graph Enabling Data Intelligent Applications using Semantic Data Modelling A data for Digital Twin and BIM. The knowledge graph represents a collection of interlinked descriptions of real-world entities like objects, events. The graph is processable by the machine as well as humans. JOB REQUIREMENTS/ SKILLS: Experience in Data Engineering and Ontology Expert in Data modelling, high level architecture designs and concepts with 2-7 years of experience Strong Python programming skills Good experience in ETL (Extract, Transform, Load) operations using Python and loading to graph DB. Expert in converting data into RDF. Expert in understanding of triple store database concepts and implementation in Graph DB (like Blazegraph) Supports new developments in Digitalization which are based on 3D, 4D and 5Ddata Expert in converting data from different formats like xml, excel etc into RDF (Resource Description Framework) Expert in various relational databases and NoSQL databases like MongoDB, semantics, triple stores etc Hands on working experience in Semantic Web standards from W3C: RDF, RDFS, OWL, SPARQL etc. Large scale data visualizations on the lines of d3js, Graphviz. Advance Level knowledge on data integration and complex data workflows Mandatory Skills: RDF, RDFS, OWL, SPARQL, Data Modeling Minimum 1 year of relevant (only hands on experience is countable, not just knowledge or awareness) experience on above mandatory technology stack Total experience should be about 2-7 years of experience Create a better #TomorrowWithUs! This role is in Bangalore, where youll get the chance to work with teams impacting entire cities, countries and the craft of things to come.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. What you will do Role Description: We are seeking a Senior Data Engineer with expertise in Graph Data technologies to join our data engineering team and contribute to the development of scalable, high-performance data pipelines and advanced data models that power next-generation applications and analytics. This role combines core data engineering skills with specialized knowledge in graph data structures, graph databases, and relationship-centric data modeling, enabling the organization to leverage connected data for deep insights, pattern detection, and advanced analytics use cases. The ideal candidate will have a strong background in data architecture, big data processing, and Graph technologies and will work closely with data scientists, analysts, architects, and business stakeholders to design and deliver graph-based data engineering solutions. Roles & Responsibilities: Design, build, and maintain robust data pipelines using Databricks (Spark, Delta Lake, PySpark) for complex graph data processing workflows. Own the implementation of graph-based data models, capturing complex relationships and hierarchies across domains. Build and optimize Graph Databases such as Stardog, Neo4j, Marklogic or similar to support query performance, scalability, and reliability. Implement graph query logic using SPARQL, Cypher, Gremlin, or GSQL, depending on platform requirements. Collaborate with data architects to integrate graph data with existing data lakes, warehouses, and lakehouse architectures. Work closely with data scientists and analysts to enable graph analytics, link analysis, recommendation systems, and fraud detection use cases. Develop metadata-driven pipelines and lineage tracking for graph and relational data processing. Ensure data quality, governance, and security standards are met across all graph data initiatives. Mentor junior engineers and contribute to data engineering best practices, especially around graph-centric patterns and technologies. Stay up to date with the latest developments in graph technology, graph ML, and network analytics. What we expect of you Must-Have Skills: Hands-on experience in Databricks, including PySpark, Delta Lake, and notebook-based development. Hands-on experience with graph database platforms such as Stardog, Neo4j, Marklogic etc. Strong understanding of graph theory, graph modeling, and traversal algorithms Proficiency in workflow orchestration, performance tuning on big data processing Strong understanding of AWS services Ability to quickly learn, adapt and apply new technologies with strong problem-solving and analytical skills Excellent collaboration and communication skills, with experience working with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Good to have deep expertise in Biotech & Pharma industries Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Master’s degree and 3 to 4 + years of Computer Science, IT or related field experience Bachelor’s degree and 5 to 8 + years of Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation. Apply now for a career that defies imagination Objects in your future are closer than they appear. Join us. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly

Senior Data Engineer What you will do Let’s do this. Let’s change the world. In this vital role you will contribute to the development of scalable, high-performance data pipelines and advanced data models that power next-generation applications and analytics. This role combines core data engineering skills with specialized knowledge in graph data structures, graph databases, and relationship-centric data modeling, enabling the organization to leverage connected data for deep insights, pattern detection, and advanced analytics use cases. The ideal candidate will have a solid background in data architecture, big data processing, and Graph technologies and will work closely with data scientists, analysts, architects, and business stakeholders to design and deliver graph-based data engineering solutions. . Roles & Responsibilities: Design, build, and maintain robust data pipelines using Databricks (Spark, Delta Lake, PySpark) for complex graph data processing workflows. Lead the implementation of graph-based data models, capturing complex relationships and hierarchies across domains. Build and optimize Graph Databases such as Stardog, Neo4j, Marklogic or similar to support query performance, scalability, and reliability. Implement graph query logic using SPARQL, Cypher, Gremlin, or GSQL, depending on platform requirements. Collaborate with data architects to integrate graph data with existing data lakes, warehouses, and lakehouse architectures. Work closely with data scientists and analysts to enable graph analytics, link analysis, recommendation systems, and fraud detection use cases. Develop metadata-driven pipelines and lineage tracking for graph and relational data processing. Ensure data quality, governance, and security standards are met across all graph data initiatives. Mentor junior engineers and contribute to data engineering best practices, especially around graph-centric patterns and technologies. Stay up to date with the latest developments in graph technology, graph ML, and network analytics. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Master’s degree and 4 to 6 years of Computer Science, IT or related field experience Bachelor’s degree and 6 to 8 years of Computer Science, IT or related field experience Preferred Qualifications: Must-Have Skills: Hands-on experience in Databricks, including PySpark, Delta Lake, and notebook-based development. Hands-on experience with graph database platforms such as Stardog, Neo4j, Marklogic etc. Good understanding of graph theory, graph modeling, and traversal algorithms Proficiency in workflow orchestration, performance tuning on big data processing Good understanding of AWS services Ability to quickly learn, adapt and apply new technologies with strong problem-solving and analytical skills Excellent collaboration and communication skills, with experience working with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Good-to-Have Skills: Good to have deep expertise in Biotech & Pharma industries Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Project Role : Application Architect Project Role Description : Provide functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Must have skills : Manufacturing Operations Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : BTech BE Job Title:Industrial Data Architect Summary :We are seeking a highly skilled and experienced Industrial Data Architect with a proven track record in providing functional and/or technical expertise to plan, analyse, define and support the delivery of future functional and technical capabilities for an application or group of applications. Well versed with OT data quality, Data modelling, data governance, data contextualization, database design, and data warehousing. Must have Skills:Domain knowledge in areas of Manufacturing IT OT in one or more of the following verticals Automotive, Discrete Manufacturing, Consumer Packaged Goods, Life ScienceKey Responsibilities: Industrial Data Architect will be responsible for developing and overseeing the industrial data architecture strategies to support advanced data analytics, business intelligence, and machine learning initiatives. This role involves collaborating with various teams to design and implement efficient, scalable, and secure data solutions for industrial operations. Focused on designing, building, and managing the data architecture of industrial systems. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Own the offerings and assets on key components of data supply chain, data governance, curation, data quality and master data management, data integration, data replication, data virtualization. Create scalable and secure data structures, integrating with existing systems and ensuring efficient data flow. Qualifications: Data Modeling and Architecture:oProficiency in data modeling techniques (conceptual, logical, and physical models).oKnowledge of database design principles and normalization.oExperience with data architecture frameworks and methodologies (e.g., TOGAF). Database Technologies:oRelational Databases:Expertise in SQL databases such as MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.oNoSQL Databases:Experience with at least one of the NoSQL databases like MongoDB, Cassandra, and Couchbase for handling unstructured data.oGraph Databases:Proficiency with at least one of the graph databases such as Neo4j, Amazon Neptune, or ArangoDB. Understanding of graph data models, including property graphs and RDF (Resource Description Framework).oQuery Languages:Experience with at least one of the query languages like Cypher (Neo4j), SPARQL (RDF), or Gremlin (Apache TinkerPop). Familiarity with ontologies, RDF Schema, and OWL (Web Ontology Language). Exposure to semantic web technologies and standards. Data Integration and ETL (Extract, Transform, Load):oProficiency in ETL tools and processes (e.g., Talend, Informatica, Apache NiFi).oExperience with data integration tools and techniques to consolidate data from various sources. IoT and Industrial Data Systems:oFamiliarity with Industrial Internet of Things (IIoT) platforms and protocols (e.g., MQTT, OPC UA).oExperience with either of IoT data platforms like AWS IoT, Azure IoT Hub, and Google Cloud IoT Core.oExperience working with one or more of Streaming data platforms like Apache Kafka, Amazon Kinesis, Apache FlinkoAbility to design and implement real-time data pipelines. Familiarity with processing frameworks such as Apache Storm, Spark Streaming, or Google Cloud Dataflow.oUnderstanding of event-driven design patterns and practices. Experience with message brokers like RabbitMQ or ActiveMQ.oExposure to the edge computing platforms like AWS IoT Greengrass or Azure IoT Edge AI/ML, GenAI:oExperience working on data readiness for feeding into AI/ML/GenAI applicationsoExposure to machine learning frameworks such as TensorFlow, PyTorch, or Keras. Cloud Platforms:oExperience with cloud data services from at least one of the providers like AWS (Amazon Redshift, AWS Glue), Microsoft Azure (Azure SQL Database, Azure Data Factory), and Google Cloud Platform (BigQuery, Dataflow). Data Warehousing and BI Tools:oExpertise in data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google BigQuery).oProficiency with Business Intelligence (BI) tools such as Tableau, Power BI, and QlikView. Data Governance and Security:oUnderstanding of data governance principles, data quality management, and metadata management.oKnowledge of data security best practices, compliance standards (e.g., GDPR, HIPAA), and data masking techniques. Big Data Technologies:oExperience in big data platforms and tools such as Hadoop, Spark, and Apache Kafka.oUnderstanding of distributed computing and data processing frameworks. Excellent Communication:Superior written and verbal communication skills, with the ability to effectively articulate complex technical concepts to diverse audiences. Problem-Solving Acumen:A passion for tackling intricate challenges and devising elegant solutions. Collaborative Spirit:A track record of successful collaboration with cross-functional teams and stakeholders. Certifications:AWS Certified Data Engineer Associate / Microsoft Certified:Azure Data Engineer Associate / Google Cloud Certified Professional Data Engineer certification is mandatory Minimum of 14-18 years progressive information technology experience. Qualifications BTech BE

Project Role : Data Platform Engineer Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : Neo4j Good to have skills : Database Management Minimum 3 year(s) of experience is required Educational Qualification : Minimum 15 years of full time education Roles & Responsibilities:1. Implementation of new Enhancement to existing UI2. Migration of Code to updated frameworks from unsupported and planned to be retired frameworks3. Refactor Code for Maintenance and stability 4. Migration to GraphDB 5. Bugfix of defects Professional & Technical Skills:1. 6+ years of IT experience2. Strong & proven development skills in RDF Triple Store:Apache JENA TBD & FUSEKI, Query (SPARQL, SPASQL), Ontotext GraphDB, Knowledge Graphs, Dictionaries/Ontologies (RDF, RDFS, OWL, SKOS, Schema.org), Logical Rules (SWRL, SPIN, R2RML, SHACL)3. Excellent analytical and problem-solving skills 4. Prior experience of working in Agile work environment5. Good to have experience on NoSQL based databases like MongoDB, Neo4j etc.,6. Strong communication skills Additional Information: The candidate should have a minimum of 3 years of experience in Neo4j The ideal candidate will possess a strong educational background in computer science or a related field, along with a proven track record of delivering impactful data-driven solutions. This position is based at our Pune office. Qualification Minimum 15 years of full time education

Job Title - Senior Data Engineer (Graph DB specialist)+ Specialist + Global Song Management Level :9,Specialist Location:Kochi, Coimbatore Must have skills: Data Modeling Techniques and Methodologies Good to have skills:Proficiency in Python and PySpark programming. Job Summary :We are seeking a highly skilled Data Engineer with expertise in graph databases to join our dynamic team. The ideal candidate will have a strong background in data engineering, graph querying languages, and data modeling, with a keen interest in leveraging cutting-edge technologies like vector databases and LLMs to drive functional objectives. Your responsibilities will include: Design, implement, and maintain ETL pipelines to prepare data for graph-based structures. Develop and optimize graph database solutions using querying languages such as Cypher, SPARQL, or GQL. Neo4J DB experience is preferred. Build and maintain ontologies and knowledge graphs, ensuring efficient and scalable data modeling. Integrate vector databases and implement similarity search techniques, with a focus on Retrieval-Augmented Generation (RAG) methodologies and GraphRAG. Collaborate with data scientists and engineers to operationalize machine learning models and integrate with graph databases. Work with Large Language Models (LLMs) to achieve functional and business objectives. Ensure data quality, integrity, and security while delivering robust and scalable solutions. Communicate effectively with stakeholders to understand business requirements and deliver solutions that meet objectives. Roles & Responsibilities: Experience:At least 5 years of hands-on experience in data engineering. With 2 years of experience working with Graph DB. Programming: Querying:Advanced knowledge of Cypher, SPARQL, or GQL querying languages. ETL Processes:Expertise in designing and optimizing ETL processes for graph structures. Data Modeling:Strong skills in creating ontologies and knowledge graphs.Presenting data for Graph RAG based solutions Vector Databases:Understanding of similarity search techniques and RAG implementations. LLMs:Experience working with Large Language Models for functional objectives. Communication:Excellent verbal and written communication skills. Cloud Platforms:Experience with Azure analytics platforms, including Function Apps, Logic Apps, and Azure Data Lake Storage (ADLS). Graph Analytics:Familiarity with graph algorithms and analytics. Agile Methodology:Hands-on experience working in Agile teams and processes. Machine Learning:Understanding of machine learning models and their implementation. Professional & Technical Skills: Additional Information: (do not remove the hyperlink) Qualifications Experience: Minimum 5-10 year(s) of experience is required Educational Qualification: Any graduation / BE / B Tech

Project Role : Application Architect Project Role Description : Provide functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Must have skills : Manufacturing Operations Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : BTech BE Job Title:Industrial Data ArchitectSummary:We are seeking a highly skilled and experienced Industrial Data Architect with a proven track record in providing functional and/or technical expertise to plan, analyse, define and support the delivery of future functional and technical capabilities for an application or group of applications. Well versed with OT data quality, Data modelling, data governance, data contextualization, database design, and data warehousing.Must have Skills:Domain knowledge in areas of Manufacturing IT OT in one or more of the following verticals Automotive, Discrete Manufacturing, Consumer Packaged Goods, Life ScienceKey Responsibilities: Industrial Data Architect will be responsible for developing and overseeing the industrial data architecture strategies to support advanced data analytics, business intelligence, and machine learning initiatives. This role involves collaborating with various teams to design and implement efficient, scalable, and secure data solutions for industrial operations. Focused on designing, building, and managing the data architecture of industrial systems. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Own the offerings and assets on key components of data supply chain, data governance, curation, data quality and master data management, data integration, data replication, data virtualization. Create scalable and secure data structures, integrating with existing systems and ensuring efficient data flow.Qualifications: Data Modeling and Architecture:oProficiency in data modeling techniques (conceptual, logical, and physical models).oKnowledge of database design principles and normalization.oExperience with data architecture frameworks and methodologies (e.g., TOGAF). Database Technologies:oRelational Databases:Expertise in SQL databases such as MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.oNoSQL Databases:Experience with at least one of the NoSQL databases like MongoDB, Cassandra, and Couchbase for handling unstructured data.oGraph Databases:Proficiency with at least one of the graph databases such as Neo4j, Amazon Neptune, or ArangoDB. Understanding of graph data models, including property graphs and RDF (Resource Description Framework).oQuery Languages:Experience with at least one of the query languages like Cypher (Neo4j), SPARQL (RDF), or Gremlin (Apache TinkerPop). Familiarity with ontologies, RDF Schema, and OWL (Web Ontology Language). Exposure to semantic web technologies and standards. Data Integration and ETL (Extract, Transform, Load):oProficiency in ETL tools and processes (e.g., Talend, Informatica, Apache NiFi).oExperience with data integration tools and techniques to consolidate data from various sources. IoT and Industrial Data Systems:oFamiliarity with Industrial Internet of Things (IIoT) platforms and protocols (e.g., MQTT, OPC UA).oExperience with either of IoT data platforms like AWS IoT, Azure IoT Hub, and Google Cloud IoT Core.oExperience working with one or more of Streaming data platforms like Apache Kafka, Amazon Kinesis, Apache FlinkoAbility to design and implement real-time data pipelines. Familiarity with processing frameworks such as Apache Storm, Spark Streaming, or Google Cloud Dataflow.oUnderstanding of event-driven design patterns and practices. Experience with message brokers like RabbitMQ or ActiveMQ.oExposure to the edge computing platforms like AWS IoT Greengrass or Azure IoT Edge AI/ML, GenAI:oExperience working on data readiness for feeding into AI/ML/GenAI applicationsoExposure to machine learning frameworks such as TensorFlow, PyTorch, or Keras. Cloud Platforms:oExperience with cloud data services from at least one of the providers like AWS (Amazon Redshift, AWS Glue), Microsoft Azure (Azure SQL Database, Azure Data Factory), and Google Cloud Platform (BigQuery, Dataflow). Data Warehousing and BI Tools:oExpertise in data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google BigQuery).oProficiency with Business Intelligence (BI) tools such as Tableau, Power BI, and QlikView. Data Governance and Security:oUnderstanding of data governance principles, data quality management, and metadata management.oKnowledge of data security best practices, compliance standards (e.g., GDPR, HIPAA), and data masking techniques. Big Data Technologies:oExperience in big data platforms and tools such as Hadoop, Spark, and Apache Kafka.oUnderstanding of distributed computing and data processing frameworks. Excellent Communication:Superior written and verbal communication skills, with the ability to effectively articulate complex technical concepts to diverse audiences. Problem-Solving Acumen:A passion for tackling intricate challenges and devising elegant solutions. Collaborative Spirit:A track record of successful collaboration with cross-functional teams and stakeholders. Certifications:AWS Certified Data Engineer Associate / Microsoft Certified:Azure Data Engineer Associate / Google Cloud Certified Professional Data Engineer certification is mandatory Minimum of 14-18 years progressive information technology experience. Qualifications BTech BE

Project Role : Data Platform Engineer Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : Neo4j Good to have skills : Database Management Minimum 3 year(s) of experience is required Educational Qualification : Minimum 15 years of full time education Roles & Responsibilities:1. Implementation of new Enhancement to existing UI2. Migration of Code to updated frameworks from unsupported and planned to be retired frameworks3. Refactor Code for Maintenance and stability 4. Migration to GraphDB 5. Bugfix of defects Professional & Technical Skills:1. 6+ years of IT experience2. Strong & proven development skills in RDF Triple Store:Apache JENA TBD & FUSEKI, Query (SPARQL, SPASQL), Ontotext GraphDB, Knowledge Graphs, Dictionaries/Ontologies (RDF, RDFS, OWL, SKOS, Schema.org), Logical Rules (SWRL, SPIN, R2RML, SHACL)3. Excellent analytical and problem-solving skills 4. Prior experience of working in Agile work environment5. Good to have experience on NoSQL based databases like MongoDB, Neo4j etc.,6. Strong communication skills Additional Information: The candidate should have a minimum of 3 years of experience in Neo4j The ideal candidate will possess a strong educational background in computer science or a related field, along with a proven track record of delivering impactful data-driven solutions. This position is based at our Pune office. Qualification Minimum 15 years of full time education