5 Gremlin Jobs

Profile : Resiliency Testing Experience: 4.5 - 8 Years Location: Bangalore Notice Period: max 30 days Minimum of 4.5 years of related experience Bachelor's degree preferred or equivalent experience Basic java / Selenium development skills with significant experience applying those skills in test environments. Chaos Engineering / Resiliency Testing experience for distributed applications using tools like Gremlin or AWS FIS Able to interpret technical designs and specifications and design automated solutions accordingly. Capable of working on multiple work streams concurrently in a fast-paced environment with multi-tasking and context switching. Experience on API and AWS tools a plus Interested candidates kindly share the Update CV at pooja.roy@esolgobal.com or WhatsApp your update CV : 7814103214.

What You'll Do Develop a basic understanding of the product being delivered Develop a strong understanding of the logical architecture and technical design of the applications being supported Work closely with application development, IT Architecture, and other key partners to understand application design and baseline against the defined resiliency principles Create resiliency test scenarios and synthetic test data as per the data distribution and volume requirements Develop resiliency test automation scripts leveraging Gremlin / in-house resiliency test automation framework Contribute to the technical aspects of Delivery Pipeline adoption Track defects to closure, report test results, continuously monitor execution milestones and escalate as required Adhere to all process standards, guidelines, and documented procedures Talents Needed for Success: Minimum of 4.5 years of related experience Bachelor's degree preferred or equivalent experience Basic java / Selenium development skills with significant experience applying those skills in test environments. Chaos Engineering / Resiliency Testing experience for distributed applications using tools like Gremlin or AWS FIS Able to interpret technical designs and specifications and design automated solutions accordingly. Capable of working on multiple work streams concurrently in a fast-paced environment with multi-tasking and context switching. Experience on API and AWS tools a plus Feel free to reach out at Gurpreet.singh@esolglobal.com / 7087000690 (WhatsApp)

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 Masters degree and 3 to 4 + years of Computer Science, IT or related field experience Bachelors 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.

Your Responsibilities: Driving the capability building for resiliency testing targeted toward modernization initiatives, common capabilities framework, reference architectures Working closely with application development, IT Architecture, Application Resiliency Foundation and other key partners ensuring end-to-end Application resiliency while upholding ETE policy, procedures and standards Developing and supporting the ETE Resiliency services / work such as the Resiliency Test Scorecard, Failure Mode Analysis, Test Scenarios Improving, setting the direction for the resiliency test automation framework, publishing reusable artifacts to the Developer Marketplace Capture technical requirements, assessing capabilities and mapping to organizational resiliency principles to determine resiliency characteristics of applications. Chip in to strategy discussions and decisions on overall application design and best approach for implementing cloud, and on premises solutions. Focus on continuous improvement practices as the need arises to meet system resiliency imperatives. Define high availability and resilience standards and guidelines for embracing technologies from AWS and other service providers. Mitigates risk by following established procedures and supervising controls, spotting key errors and demonstrating strong ethical behavior. Experience: 7 + Years Location: Hyderabad Additional Information Talents Needed for Success: Minimum of 7 years of related experience Bachelors degree required; Masters preferred and/or equivalent experience Minimum of 3 years experience in testing / architecting and delivering cloud-based solutions Must have expertise with industry patterns, chaos engineering methodologies, and techniques across the disaster recovery subject areas Specialist in highly available architecture and solution implementation Chaos Engineering / Resiliency Testing experience for distributed applications using tools like Gremlin or Cavisson NetHavoc Enterprise Java technologies, tools and system architectures; Splunk and application monitoring tooling such as Dynatrace / AppDynamics

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