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The Knowledge Graph Architect is responsible for designing, developing, and implementing knowledge graph technologies to enhance organizational data understanding and decision-making capabilities. This role involves collaborating with data scientists, engineers, and business stakeholders to integrate complex data into accessible and insightful knowledge graphs.

Work you’ll do

1. Design and develop scalable and efficient knowledge graph architectures.

2. Implement knowledge graph integration with existing data systems and business processes.

3. Lead the ontology design, data modeling, and schema development for knowledge representation.

4. Collaborate with IT and business units to understand data needs and deliver comprehensive knowledge graph solutions.

5. Manage the lifecycle of knowledge graph data, including quality, consistency, and updates.

6. Provide expertise in semantic technologies and machine learning to enhance data interconnectivity and retrieval.

7. Develop and maintain documentation and specifications for system architectures and designs.

8. Stay updated with the latest industry trends in knowledge graph technologies and data management.

The Team

Innovation & Technology anticipates how technology will shape the future and begins building future capabilities and practices today. I&T drives the Ideation, Incubation and scale of hybrid businesses and tech enabled offerings at prioritized offering portfolio and industry interactions.

It drives cultural and capability transformation from solely services – based businesses to hybrid businesses. While others bet on the future, I&T builds it with you.

I&T encompasses many teams—dreamers, designers, builders—and partners with the business to bring a unique POV to deliver services and products for clients.

Qualifications and Experience

Required:

1. Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.

2. 6-10 years of professional experience in data engineering with Proven experience in designing and implementing knowledge graph systems.

3. Strong understanding of semantic web technologies (RDF, SPARQL, GraphQL,OWL, etc.).

4. Experience with graph databases such as Neo4j, Amazon Neptune, or others.

5. Proficiency in programming languages relevant to data management (e.g., Python, Java, Javascript).

6. Excellent analytical and problem-solving abilities.

7. Strong communication and collaboration skills to work effectively across teams.

Preferred:

1. Experience with machine learning and natural language processing.

2. Experience with Industry 4.0 technologies and principles

3. Prior exposure to cloud platforms and services like AWS, Azure, or Google Cloud.

4. Experience with containerization technologies like Docker and Kubernetes

Key responsibilities

• Design, build, and maintain robust CI/CD pipelines using Azure DevOps Services (Azure Pipelines) and Git-based workflows.

• Implement and manage infrastructure as code (IaC) using ARM templates, Bicep, and/or Terraform for repeatable environment provisioning.

• Containerize applications (Docker) and manage container orchestration platforms such as AKS (Azure Kubernetes Service).

• Automate build, test, release, and rollback processes; integrate automated testing and quality gates into pipelines.

• Monitor and improve platform reliability and observability using logging and monitoring tools (e.g., Azure Monitor, Application Insights, Prometheus, Grafana).

• Drive platform security and compliance through pipeline controls, secrets management (Key Vault / Vault), and secure configuration practices.

• Implement cost-optimization and governance for Azure resources (tags, policies, budgets).

• Troubleshoot build/release failures, production incidents, and performance bottlenecks; perform root-cause analysis and implement permanent fixes.

• Mentor developers in Git workflows, pipeline authoring, best practices for IaC, and cloud-native design.

• Maintain clear documentation: runbooks, deployment playbooks, architecture diagrams, and pipeline templates. 

Required skills & experience

• 4+ years hands-on experience working with Azure and cloud-native application delivery.

• Deep experience with Azure DevOps (Repos, Pipelines, Artifacts, Boards).

• Strong IaC skills with Terraform, ARM templates, or Bicep.

• Solid experience with CI/CD design and YAML pipeline authoring.

• Practical knowledge of containerization (Docker) and Kubernetes — preferably AKS.

• Scripting skills: PowerShell, Bash, and/or Python for automation.

• Experience with Git workflows (branching strategies, PRs, code reviews).

• Familiarity with configuration management and secrets management (Azure Key Vault, HashiCorp Vault).

• Understanding of networking, identity (Azure AD), and security fundamentals in Azure.

• Strong troubleshooting, debugging, and incident response skills.

• Good collaboration and communication skills; ability to work across teams.

Certification

AZ-400: Microsoft Certified: DevOps Engineer Expert or AZ-104 or AZ 305 or Terraform Associate.

Job Description:      

• Extensive experience in Appian BPM application development
• Knowledge of Appian architecture and its objects best practices
• Participate in analysis, design, and new development of Appian based applications
• Team leadership and provide technical leadership to Scrum teams
• Must be able to multi-task, work in a fast-paced environment and ability to resolve problems faced by team
• Build applications: interfaces, process flows, expressions, data types, sites, integrations,
• Proficient with SQL queries and with accessing data present in DB tables and views
• Experience in Analysis, Designing process models, Records, Reports, SAIL, forms, gateways, smart services, integration services and web services
• Experience working with different Appian Object types, query rules, constant rules and expression rules

• At least 6 years of experience in Implementing BPM solutions using Appian 19.x or higher
• Over 8 years in Implementing IT solutions using BPM or integration technologies
• Certification Mandatory- L1 and L2 a
• Experience in Scrum/Agile methodologies with Enterprise level application development projects
• Good understanding of database concepts and strong working knowledge any one of the major databases e g Oracle SQL Server MySQL

• Appian BPM application development on version 19.x or higher
• Experience of integrations using web services e g XML REST WSDL SOAP API JDBC JMS
• Good leadership skills and the ability to lead a team of software engineers technically
• Experience working in Agile Scrum teams
• Good Communication skills

Job Description:

1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges

a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem

b. Improve Model accuracy to deliver greater business impact

c.Estimate business impact due to deployment of model

2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge

3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines

4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch 

5.Experience in using Deep learning models with text, speech, image and video data

a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc

b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV

c.Knowledge of State of the art Deep learning algorithms

6.Optimize and tune Deep Learnings model for best possible accuracy

7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau

8.Work with application teams, in deploying models on cloud as a service or on-prem

a.Deployment of models in Test / Control framework for tracking

b.Build CI/CD pipelines for ML model deployment

9.Integrating AI&ML models with other applications using REST APIs and other connector technologies

10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

· Technology/Subject Matter Expertise

• Sufficient expertise in machine learning, mathematical and statistical sciences
• Use of versioning & Collaborative tools like Git / Github
• Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
• Develop prototype level ideas into a solution that can scale to industrial grade strength
• Ability to quantify & estimate the impact of ML models.

· Softskills Profile

• Curiosity to think in fresh and unique ways with the intent of breaking new ground.
• Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
• Ability to think ahead, and anticipate the needs for solving the problem will be important

·        Ability to communicate key messages effectively, and articulate strong opinions in large forums

· Desirable Experience:

• Keen contributor to open source communities, and communities like Kaggle
• Ability to process Huge amount of Data using Pyspark/Hadoop
• Development & Application of Reinforcement Learning
• Knowledge of Optimization/Genetic Algorithms
• Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
• Optimize and tune deep learning model for best possible accuracy
• Understanding of stream data processing, RPA, edge computing, AR/VR etc
• Appreciation of digital ethics, data privacy will be important
• Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
• Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus

Job Location: Hyderabad/Bangalore/ Chennai/Pune/Nagpur

Notice period: Immediate - 15 days

1.      Python Developer with Snowflake

Job Description :

1. 5.5+ years of Strong Python Development Experience with Snowflake.
2. Strong hands of experience with SQL ability to write complex queries.
3. Strong understanding of how to connect to Snowflake using Python, should be able to handle any type of files
4.  Development of Data Analysis, Data Processing engines using Python
5. Good Experience in Data Transformation using Python. 
6.  Experience in Snowflake data load using Python.
7.  Experience in creating user-defined functions in Snowflake.
8.  Snowsql implementation.
9.  Knowledge of query performance tuning will be added advantage.
10. Good understanding of Datawarehouse (DWH) concepts.
11.  Interpret/analyze business requirements & functional specification
12.  Good to have DBT, FiveTran, and AWS Knowledge.

JOB Role : Senior Platform Consultant

Essential Skills :

• Expertise in SFMC Email Marketing Tool
• Good Experience in SQL
• Experience in Data model design
• Expertise in Campaign Orchestration
• Life cycle programs and personalization
• Expertise in Marketing data optimization and List cleansing
• Experience in Data optimization and Hygiene
• Experience in Personalization in campaigns
• Good Business understanding of Digital Marketing
• Excellent communication skills
• Preferably with SFMC Certification (Marketing Cloud Specialist or Email Specialist)

Role Description :

• The person will be required to work on SFMC platform for creating and executing marketing campaigns.
• Ability to work independently and work directly with Marketing teams
• Drive the strategy for the email program to deliver strong engagement and results, through audience segmentation, deliverability, best practices, and data analysis.
• Analyse the effectiveness of Digital Marketing deliverables, measures against objectives and reports results.
• Flawless delivery of daily campaigns, troubleshoot issues that arise and implement solutions to mitigate future problems