• Job Summary:
We are seeking a skilled Data Engineer with strong experience in SQL, Python, Tableau, and ETL tools to design, build, and maintain reliable data pipelines and analytics solutions. This role focuses on ensuring data quality, enabling scalable data workflows, and supporting business intelligence and reporting needs.
• Roles and Responsibilities
• Collect, clean and validate data from multiple sources to ensure accuracy and reliability • Develop ETL Pipelines to process the data from multiple sources such as csv,flat files and live databases • Build, maintain, and optimize SQL queries, stored procedures, and data pipelines • Use Python for data manipulation, automation, statistical analysis, and exploratory data analysis • Collaborate with cross functional teams (data analysts, product teams, business stakeholders) to understand data requirements. • Perform trend analysis, forecasting, and KPI reporting • Support data governance, documentation, and metadata management • Troubleshoot data issues and identify opportunities for process improvement • Work with cross functional teams such as IT, engineering, operations, and finance • Staying up to date with emerging technologies and trends in data analytics space and recommending innovative solutions to improve data efficiency and quality • Manage the changes and refresh the data for all the Dashboards
Responsibilities
• Required Skills
What you need to Bring: Bachelor’s/master’s in engineering, Computer Science, or equivalent experience. 3 to 5 years of experience in the IT industry, experience in Data space is a must. Technical Skills (Experience Level: 3 to 5 years) SQL & Database Management: Expertise in querying, transforming, and optimizing data. You should have solid experience in relational databases (PostgreSQL, MySQL, Oracle) and NoSQL (MongoDB, Cassandra) databases. Solid experience in SQL Programming: Strong in Python programming for automation and pipeline development. good to have scala. ETL/ELT Frameworks: Building pipelines to Extract, Transform, and Load data using any leading industry ETL tools such as DataIQ, Informatica, Data stage, Alteryx Data Processing Framework: Solid experience in processing large-scale data using Apache Spark or any other data processing framework. should have worked at least one project in large distributed system Data Modeling: Designing efficient schemas and understanding normalization/denormalization to ensure fast data retrieval. Good Experience in creating logical and physical data models. Version Control: Proficiency in Git is mandatory for managing code and collaborating on pipelines Cloud Platforms: Expertise in at least one cloud platform (GCP, AWS or Azure) and their specific data services. Good to have GCP experience. Orchestration: Automating and scheduling complex workflows using tools like Apache Airflow, Prefect, or Dagster. Data Warehousing: Knowledge of modern cloud-native warehouses like Snowflake, Google Big Query, Teradata or Amazon Redshift Real-time Processing: Knowledge of handling data streams as they arrive using Kafka, Flink, or Spark Streaming. Data Governance & Security: Implementing encryption, access controls, and ensuring compliance with regulations like GDPR or HIPAA. AI/ML Integration: Building infrastructure and "feature pipelines" to support machine learning models Good to Have Technical Skills: • Knowledge or Experience using Agile methodology to perform software development. • Knowledge of ITIL Industry best practices • Knowledge of Google looker studio experience is plus. • Knowledge of any BI tool is a plus , Preferably Tableau • Knowledge of Pulse and Tableau Prep is added advantage • Knowledge of UI/UX – Figma tools is added advantage • Having Manufacturing domain experience is great value ad, but not mandatory
• Desired Skills:
What you need to Bring: Bachelor’s/master’s in engineering, Computer Science, or equivalent experience. 3 to 5 years of experience in the IT industry, experience in Data space is a must. Technical Skills (Experience Level: 3 to 5 years) SQL & Database Management: Expertise in querying, transforming, and optimizing data. You should have solid experience in relational databases (PostgreSQL, MySQL, Oracle) and NoSQL (MongoDB, Cassandra) databases. Solid experience in SQL Programming: Strong in Python programming for automation and pipeline development. good to have scala. ETL/ELT Frameworks: Building pipelines to Extract, Transform, and Load data using any leading industry ETL tools such as DataIQ, Informatica, Data stage, Alteryx Data Processing Framework: Solid experience in processing large-scale data using Apache Spark or any other data processing framework. should have worked at least one project in large distributed system Data Modeling: Designing efficient schemas and understanding normalization/denormalization to ensure fast data retrieval. Good Experience in creating logical and physical data models. Version Control: Proficiency in Git is mandatory for managing code and collaborating on pipelines Cloud Platforms: Expertise in at least one cloud platform (GCP, AWS or Azure) and their specific data services. Good to have GCP experience. Orchestration: Automating and scheduling complex workflows using tools like Apache Airflow, Prefect, or Dagster. Data Warehousing: Knowledge of modern cloud-native warehouses like Snowflake, Google Big Query, Teradata or Amazon Redshift Real-time Processing: Knowledge of handling data streams as they arrive using Kafka, Flink, or Spark Streaming. Data Governance & Security: Implementing encryption, access controls, and ensuring compliance with regulations like GDPR or HIPAA. AI/ML Integration: Building infrastructure and "feature pipelines" to support machine learning models Good to Have Technical Skills: • Knowledge or Experience using Agile methodology to perform software development. • Knowledge of ITIL Industry best practices • Knowledge of Google looker studio experience is plus. • Knowledge of any BI tool is a plus , Preferably Tableau • Knowledge of Pulse and Tableau Prep is added advantage • Knowledge of UI/UX – Figma tools is added advantage • Having Manufacturing domain experience is great value ad, but not mandatory
• Soft Skills :
• Excellent problem-solving and analytical skills • Strong communication and collaboration skills • Ability to work independently and as part of a global team. • Self-motivated and able to work in a fast-paced environment. • Detail-oriented and committed to delivering high-quality work. • Display one-team behavior while thinking end to end solutioning.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
• Job Summary:
• Experience in design and development of an Embedded Systems. • Expert knowledge in developing modular application software using C for an Embedded Linux system. • Experience in writing multithreaded application software’s and libraries for Embedded Linux system. • Good knowledge of Hardware/Software interfaces and reading schematics. • Experience in communication interfaces like CAN, RS232, I2C, SPI, Bluetooth/BLE & GSM AT Commands. • Experience in standard automotive communication protocols like J1939. • Experience in using various tools like static code analysis, run time debugging tools like GDB & memory debugging tools like Valgrind is an added advantage • Good working knowledge in agile-based product development methodology. • Effective communication, interpersonal, analytical and problem-solving skills. • Experience in Telematics domain is an added advantage. • A degree in engineering with 5+ years of experience in embedded software development.
Responsibilities
• Roles and Responsibilities
Software development and testing
• Required Skills
C, Embedded Linux application programming, multi process and multi thread environment, BLE, CAN
• Desired Skills:
C, Embedded Linux application programming, multi process and multi thread environment, BLE, CAN
• Soft Skills :
Good verbal and written communications
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Network Design & Delivery
· Lead end-to-end delivery of enterprise network projects covering LAN, Wireless, and SD-WAN technologies.
· Perform network scoping, solution design, and implementation aligned with approved architecture standards.
· Create and review HLDs, LLDs, BOMs & Runbooks, implementation plans, and handover documentation.
· Drive Network Refresh, EOL/EOS remediation, and technology modernization initiatives.
· Ensure solutions meet performance, scalability, resiliency, standard and security requirements.
LAN & Wireless Engineering
· Deliver enterprise campus LAN solutions using Cisco (Catalyst or Meraki) switching platforms.
· Design and implement Enterprise wireless networks including Wi-Fi 5/6/6E, high-density environments, and site readiness.
· Working knowledge with NAC solutions (Cisco ISE) for wired and wireless access control.
· Support wired/wireless troubleshooting during deployment and stabilization phases.
SD-WAN & Secure Connectivity (Good to have/Working knowledge)
· Design and implement SD-WAN solutions.
· Collaborate with security teams on secure connectivity patterns, firewall integration, and segmentation.
Automation & Quality Improvement
· Contribute to network automation and standardization efforts (Ansible, templates, APIs, or vendor tools).
· Identify delivery inefficiencies and drive process, quality, and documentation improvements.
· Participate in design reviews, quality checks, and peer mentoring.
Stakeholder & Vendor Engagement
· Work directly with internal customers, project managers, and global stakeholders.
· Coordinate with OEMs, ISPs, and system integrators for implementation and issue resolution.
· Provide clear communication on project status, risks, and dependencies.
Responsibilities
Salary : Rs. 30,00,000.0 - Rs. 35,00,000.0
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Role Title
Senior AI Solution Architect
Experience: 8–12 Years (with 3+ years in AI/ML solution architecture)
Location : Chennai, India
________________________________________
Role Overview
We are seeking a Senior AI Solution Architect to lead the design and delivery of scalable, production-grade AI solutions across the enterprise. This role is responsible for defining AI architecture standards, enabling AI CoE practices, and ensuring secure, cost-efficient, and high-performance AI integrations within our enterprise ecosystem.
The ideal candidate bridges business strategy, AI engineering, and enterprise architecture.
Key Responsibilities
1. Enterprise AI Architecture
• Design end-to-end AI/GenAI architectures including:
o Data ingestion & preprocessing pipelines
o Model orchestration frameworks
o RAG architectures
o API & microservice exposure
• Define reusable AI reference architectures and accelerators.
2. AI Model Strategy & Evaluation
• Select appropriate models (OpenAI, Azure AI, open-source LLMs, custom-trained models) based on:
o Business use case
o Latency requirements
o Cost optimization
o Data sensitivity
• Establish evaluation frameworks for LLM quality, hallucination mitigation, and performance benchmarking.
3. AI Productionization (MLOps / LLMOps)
• Define CI/CD pipelines for AI deployments.
• Implement monitoring for:
o Model drift
o Prompt performance
o Token usage & cost control
o Latency & uptime
• Establish rollback and versioning strategies.
4. Polyglot & Enterprise Integration
• Architect integration of Python-based AI services into .NET and Java ecosystems.
• Design event-driven, API-first AI services.
• Ensure secure authentication (OAuth2, SAML, API Gateway patterns).
5. AI Governance & Responsible AI
• Define AI security, data privacy, and compliance standards.
• Establish guardrails for responsible AI usage.
• Collaborate with InfoSec and Legal for risk assessments.
6. Technical Leadership & AI CoE Enablement
• Mentor engineers and data scientists.
• Define coding standards and AI development best practices.
• Drive POC-to-production transformation roadmap.
Core Competencies
AI Architecture & Engineering
• Strong knowledge of LLM orchestration frameworks (LangChain, LlamaIndex or equivalent)
• Experience with RAG systems
• Understanding of embedding strategies and vector databases
• Familiarity with fine-tuning and prompt engineering
Enterprise Architecture
• Microservices & API-first architecture
• Event-driven systems
• Docker/Kubernetes
• Cloud-native AI deployments (Azure preferred)
AI Operations
• MLOps / LLMOps practices
• Monitoring & observability tools
• Cost optimization strategies for AI workloads
Leadership
• Ability to translate business problems into scalable AI solutions
• Experience contributing to AI CoE setup
• Strong stakeholder communication skills
Responsibilities
Role Title
Senior AI Solution Architect
Experience: 8–12 Years (with 3+ years in AI/ML solution architecture)
Location : Chennai, India
________________________________________
Role Overview
We are seeking a Senior AI Solution Architect to lead the design and delivery of scalable, production-grade AI solutions across the enterprise. This role is responsible for defining AI architecture standards, enabling AI CoE practices, and ensuring secure, cost-efficient, and high-performance AI integrations within our enterprise ecosystem.
The ideal candidate bridges business strategy, AI engineering, and enterprise architecture.
Key Responsibilities
1. Enterprise AI Architecture
• Design end-to-end AI/GenAI architectures including:
o Data ingestion & preprocessing pipelines
o Model orchestration frameworks
o RAG architectures
o API & microservice exposure
• Define reusable AI reference architectures and accelerators.
2. AI Model Strategy & Evaluation
• Select appropriate models (OpenAI, Azure AI, open-source LLMs, custom-trained models) based on:
o Business use case
o Latency requirements
o Cost optimization
o Data sensitivity
• Establish evaluation frameworks for LLM quality, hallucination mitigation, and performance benchmarking.
3. AI Productionization (MLOps / LLMOps)
• Define CI/CD pipelines for AI deployments.
• Implement monitoring for:
o Model drift
o Prompt performance
o Token usage & cost control
o Latency & uptime
• Establish rollback and versioning strategies.
4. Polyglot & Enterprise Integration
• Architect integration of Python-based AI services into .NET and Java ecosystems.
• Design event-driven, API-first AI services.
• Ensure secure authentication (OAuth2, SAML, API Gateway patterns).
5. AI Governance & Responsible AI
• Define AI security, data privacy, and compliance standards.
• Establish guardrails for responsible AI usage.
• Collaborate with InfoSec and Legal for risk assessments.
6. Technical Leadership & AI CoE Enablement
• Mentor engineers and data scientists.
• Define coding standards and AI development best practices.
• Drive POC-to-production transformation roadmap.
Core Competencies
AI Architecture & Engineering
• Strong knowledge of LLM orchestration frameworks (LangChain, LlamaIndex or equivalent)
• Experience with RAG systems
• Understanding of embedding strategies and vector databases
• Familiarity with fine-tuning and prompt engineering
Enterprise Architecture
• Microservices & API-first architecture
• Event-driven systems
• Docker/Kubernetes
• Cloud-native AI deployments (Azure preferred)
AI Operations
• MLOps / LLMOps practices
• Monitoring & observability tools
• Cost optimization strategies for AI workloads
Leadership
• Ability to translate business problems into scalable AI solutions
• Experience contributing to AI CoE setup
• Strong stakeholder communication skills
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
