Technical Support Analyst

Job Title : Data Engineer – Snowflake Expert

Location : Pune (Onsite)

Experience : 10+ Years

Employment Type : Contractual

Mandatory Skills : Snowflake, Advanced SQL, ETL/ELT (Snowpipe, Tasks, Streams), Data Modeling, Performance Tuning, Python, Cloud (preferably Azure), Security & Data Governance.

Job Summary :

We are seeking a seasoned Data Engineer with deep expertise in Snowflake to design, build, and maintain scalable data solutions.

The ideal candidate will have a strong background in data modeling, ETL/ELT, SQL optimization, and cloud data warehousing principles, with a passion for leveraging Snowflake to drive business insights.

Responsibilities :

• Collaborate with data teams to optimize and enhance data pipelines and models on Snowflake.
• Design and implement scalable ELT pipelines with performance and cost-efficiency in mind.
• Ensure high data quality, security, and adherence to governance frameworks.
• Conduct code reviews and align development with best practices.

Qualifications :

• Bachelor’s in Computer Science, Data Science, IT, or related field.
• Snowflake certifications (Pro/Architect) preferred.

Job Title: AI/ML Engineer – Voice (2–3 Years)

Location: Bengaluru (On-site)

Employment Type: Full-time

About Impacto Digifin Technologies

Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.

We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.

Role Overview

We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.

This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.

You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.

This role is collaborative, cross-functional, and hands-on.

Key Responsibilities

Voice AI Engineering

• Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
• Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
• Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
• Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
• Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
• Implement voice understanding modules, speech intent extraction, and context tracking.

Machine Learning & Deep Learning

• Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
• Train and fine-tune neural networks for text, speech, and multimodal tasks.
• Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
• Perform feature engineering, model evaluation, retraining, and continuous learning cycles.

NLP, LLMs & GenAI

• Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
• Work with LLM architectures for text + voice workflows
• Build GenAI-based workflows and integrate models into production systems.
• Implement RAG pipelines and agent-based systems for complex automation.

Fintech & Banking AI

• Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
• Understand fintech data structures and constraints while designing AI models.

Engineering, Deployment & Collaboration

• Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
• Build robust APIs and services for voice and ML-based functionalities.
• Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
• Document systems and contribute to internal knowledge bases and R&D.

Security & Compliance

• Follow fundamental best practices for AI security, access control, and safe data handling.
• Awareness of financial compliance standards (plus, not mandatory).
• Follow internal guidelines on PII, audio data, and model privacy.

Primary Skills (Must-Have)

Core AI

• Machine Learning fundamentals
• Deep Learning architectures
• NLP pipelines and transformers
• LLM usage and integration
• GenAI development
• Voice AI (STT, TTS, VAD, real-time pipelines)
• Audio processing fundamentals
• Model building, tuning, and retraining
• RAG systems
• AI Agents (orchestration, multi-step reasoning)

Voice Engineering

• End-to-end voice application development
• Voice calling & telephony integration (framework-agnostic)
• Realtime STT ↔ LLM ↔ TTS interactive flows
• Voice chat system development
• Voice-to-AI model integration for automation

Fintech/Banking Awareness

• High-level understanding of fintech and banking AI use cases
• Data patterns in core banking analytics (advantageous)

Programming & Engineering

• Python (strong competency)
• Cloud deployment understanding (AWS/Azure/GCP)
• API development
• Data processing & pipeline creation

Secondary Skills (Good to Have)

• MLOps & CI/CD for ML systems
• Vector databases
• Prompt engineering
• Model monitoring & evaluation frameworks
• Microservices experience
• Basic UI integration understanding for voice/chat
• Research reading & benchmarking ability

Qualifications

• 2–3 years of practical experience in AI/ML/DL engineering.
• Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
• Proven hands-on experience building ML/DL/voice pipelines.
• Experience in fintech or data-intensive domains preferred.

Soft Skills

• Clear communication and requirement understanding
• Curiosity and research mindset
• Self-driven problem solving
• Ability to collaborate cross-functionally
• Strong ownership and delivery discipline
• Ability to explain complex AI concepts simply

Job Description

We are looking for a deeply experienced ServiceNow professional who understands the internal data model and platform mechanics of ServiceNow.

This role goes beyond configuration and administration—you will work on CMDB design, data integrity, synchronization, integrations, and platform optimization across ITSM and related modules.

The ideal candidate has strong experience with CMDB tables, incident lifecycle, knowledge management, discovery, and data synchronization and can reason about ServiceNow as a platform, not just a tool. ⸻

Key Responsibilities

• Platform & CMDB Expertise
• Design, implement, and maintain CMDB architecture, including:
• Core CMDB tables (cmdb_ci, cmdb_rel_ci, subclasses)
• CI class modeling, inheritance, and relationships
• CI lifecycle management and data normalization
• Ensure CMDB data quality, consistency, and governance
• Troubleshoot and optimize CMDB performance and scalability CMDB Synchronization & Integrations

Build and manage CMDB data synchronization using:

• Discovery
• Service Mapping
• IntegrationHub
• Import Sets & Transform Maps
• Integrate ServiceNow with external systems (monitoring, asset tools, cloud providers)
• Handle reconciliation, deduplication, and source-of-truth conflicts

ITSM & Workflow Internals

• Deep understanding of Incident, Problem, Change, and Request tables and workflows
• Customize and optimize:
• Incident lifecycle
• SLA definitions and calculations
• Assignment rules and automation
• Debug complex workflow, Flow Designer, and business rule interactions

Knowledge Management

• Design and manage Knowledge Base (KB) structures and workflows
• Implement best practices for: • Article lifecycle • Access control • Versioning and approvals • Improve knowledge discoverability and reuse

Development & Customization

• Develop using server-side and client-side scripting:
• Business Rules
• Script Includes - UI Policies, Client Scripts
• Optimize scripts for performance and maintainability
• Follow best practices for scoped applications and upgrade safety

Governance & Best Practices

• Enforce ServiceNow data model and customization best practices
• Support platform upgrades and impact analysis
• Provide technical guidance and mentorship to junior ServiceNow engineers
• Work closely with product, SRE, and operations teams to align ServiceNow with operational workflows

⸻

Required Skills & Experience

Must-Have

• 7+ years of hands-on ServiceNow experience
• Strong understanding of ServiceNow internal tables and data model
• Deep expertise in CMDB architecture and synchronization
• Strong experience with ITSM modules (Incident, Problem, Change, Knowledge)
• Advanced scripting skills (JavaScript in ServiceNow context)
• Experience debugging complex platform behaviors and performance issues
• Experience with integrations and data ingestion pipelines

Good to Have

• Experience with Discovery and Service Mapping
• Exposure to ITOM, Event Management, or Observability integrations
• Experience with large-scale or multi-instance ServiceNow deployments
• ServiceNow certifications (CSA, CIS-ITSM, CIS-CMDB, Architect)
• Understanding of operational workflows (SRE, IT Ops, Incident Response)

● Experience Level: Min 2+ years

● JavaScript/Typescript and React Native.

● Experience using technologies like React Native, Redux/MobX/Saga, TypeScript, modern CSS frameworks and webpack.

● Familiarity with native build tools, like XCode, Gradle {Android Studio, IntelliJ}

● RESTful API’s, basic HTTP knowledge, GET/POST.

● Good Communication Skills

Experience : 3 to 7 Years
Number of Positions : 20

Job Location : Hyderabad

Notice : 30 Days

1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight

2. Experience in developing lambda functions with AWS Lambda

3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark

4. Should be able to code in Python and Scala.

5. Snowflake experience will be a plus

Hadoop and Hive requirements as good to have or understanding of is enough.

Learn from the best: Learn from leaders who have built Comm100 from ground up. Work under other engineers who handle different layers of the infrastructure.

Work in a data-driven team: Understand the importance of validating assumptions about user behaviour. Use various types of testing to ensure we're right (or discover where did we go wrong). Utilize data collection, enrichment, analytics, and visualizations to improve our systems.

WHO YOU ARE

To be successful in this role, you'll need to have the following skills:

Love for coding: A fanatic about writing beautiful and scalable code.

Sense of analytics: Strong analytical and troubleshooting skills. Should be resourceful, innovative, and inventive.

Dynamic: Should be comfortable in dealing with lots of moving pieces. Have exquisite attention to detail and are comfortable learning new technologies and systems.

Team player: Knack for influencing without being authoritative. Pitch in wherever the team needs help, from writing blog posts to supporting customers.

Accountability: High sense of ownership for your code and relentlessness to deliver projects with high business impact.

KEY SKILLS

• Strong computer system analysis and design skills in current methodologies and patterns including vanilla JavaScript,
• Rich experience with ReactJS, Redux, React Native, or similar library/tools.
• Obsessed with WPO (Web Performance Optimization) and web/mobile performance analysis.
• Familiar with web security, SEO, accessibility, and internationalization.
• Experience with W3C standards, HTTP protocol and web browsers.
• Experience with common tools such as front-end compilation, construction, testing, etc. (Babel, Rollup, Webpack, Jasmine, etc.)