Data & AI Consultant

Job Description

• Design and Implement Data Solutions: Lead the design, development, and implementation of scalable and secure Azure-

based data platforms, ensuring integration with various data sources and business systems. Deliver at least 2 major

projects every year with a focus on data engineering best practices.

• Optimize Data Pipelines: Build and optimize end-to-end data pipelines using Azure Data Factory, Azure Databricks, and

Azure Synapse, with an emphasis on automating data workflows. Achieve a 20% reduction in pipeline execution times

within the first 6 months.

• Cloud Infrastructure Management: Manage and maintain the Azure data environment, ensuring high availability, disaster

recovery, and cost optimization. Track and improve system uptime to exceed 99.9% reliability.

• Collaborate with Cross-Functional Teams: Partner with data scientists, data analysts, and business stakeholders to translate

business requirements into efficient data solutions. Facilitate at least 3 collaborative sessions per quarter to address key

business use cases.

• Ensure Data Security & Compliance: Implement data security measures, ensuring compliance with industry regulations

(GDPR, HIPAA, etc.) and company policies. Achieve and maintain full compliance in all data environments within the first

quarter of onboarding.

• Continuous Learning & Knowledge Sharing: Stay up-to-date with emerging Azure technologies, and mentor junior

engineers to promote knowledge sharing. Complete 1 Azure certification annually and conduct at least 2 internal

knowledge-sharing sessions per year.

• Sound knowledge of data governance practices, data quality management, and data security principles.

• Play a pivotal role in shaping our organization's data-driven journey, driving innovation through data analytics and insights.

• Optimize data storage, processing and retrieval mechanisms for performance, cost, and scalability using data storage

services (such as Azure Data Lake Storage, Azure SQL Database, etc.), data processing services (such as Azure Data Bricks,

Azure Synapse, etc.) and data visualization (PowerBI, Qlik, etc.) & integration services (Data API builder, logic apps, etc.)

• Monitor and troubleshoot data platform performance, identify and resolve issues, and provide recommendations for

continuous improvement.

• Collaborate with DevOps teams to automate deployment, configuration, and monitoring processes using Azure DevOps,

PowerShell, or other relevant tools.

• Stay up to date with the latest trends and advancements in cloud data services and provide recommendations on adopting

new technologies or features to enhance the data platform.

• Document technical designs, procedures, and guidelines for data platform engineering and operations

Knowledge, Skills & Experience

Job Experience • Bachelor's degree in Computer Science, Engineering, or a related field. Advanced

degree preferred.

• Proven 6-10 years experience in playing platform engineer or admin role

• Experience with big data technologies such as Apache Spark, Hadoop, or similar

frameworks.

• Solid understanding of cloud computing concepts and experience with cloud

infrastructure management and provisioning.

• Solid understanding of network security concepts and technologies (such as

firewalls, VPNs, intrusion detection/prevention systems, etc.) and data security

concepts and technologies (such as access controls, encryption, observability,

privacy laws/regulations, etc.)

• Experience in a Retail setup is preferred.

Required Skills The position will require someone with the following:

• Strategic Planning

Public

• Communication and Collaboration

• Problem Solving Skills A/B testing & experimentation

• SQL, BI tools, and storytelling with data

Dear Candidate,

Greeting from NAM Info Pvt Ltd.

We have a role for Data Engineer position with NAM Info.

This role will be permanent with NAM info and deploy to client

location NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA.

Work Mode: WORK FROM OFFICE

A decent hike can be provided based on current CTC

Interview Mode: Virtual

Role Descriptions:

Exp Range: 7 - 10 years

City Locations: NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA

Key Responsibilities*

Role: Data Engineer

Location: ~NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA

Skills: Digital: Databricks, Azure Data Factory

Experience Required: 8-10

Descriptions:

Good information and sound knowledge in Azure Synapse Analytics Azure Data Factory (ADF)Big Data technologies and data processing frameworks Azure Data Warehouse and associated Azure data platform services Data integration| data modelling| and performance optimization

Desire candidate

• Candidate should have valid PF.

Regards,

NAM Info 

Key Responsibilities

1. Solutioning & Proposal Development

•   Partner with Senior SMEs and Practice Leads to design end-to-end Data & AI solutions for client pursuits — contributing to structure, content, and commercial framing.

•   Build client proposals, solution documents, and program structures that are well-organized, accurate, and ready to use without significant rework.

•   Translate client requirements into structured, outcome-oriented learning journeys — adoption, capability uplift, and measurable business outcomes, not just module lists.

•   Support customized offerings across Data Engineering, AI / ML, and GenAI and Agentic AI tracks; help assemble pursuits from existing accelerators rather than rebuilding from scratch.

2. Client Engagement Support

•   Participate in client discussions, discovery calls, and requirement-gathering sessions — capture context with the rigour that makes the next conversation sharper.

•   Convert business needs into solution frameworks and delivery models with guidance from Senior SMEs; document customer priorities so Practice and Sales can act on them.

•   Support pitch decks, case studies, and success stories — buyer-specific, visually clean, and aligned to how the customer thinks about their own problem.

•   Stay engaged through the proposal cycle and handoff to delivery; ensure no requirement gets lost between discovery and execution.

3. Content & Program Structuring

•   Assist in designing curriculum outlines, learning journeys, and hands-on lab structures that hold up against real-world enterprise contexts.

•   Work with internal and external SMEs to ensure content aligns with current industry trends, real use cases, and business outcomes — not generic technology overviews.

•   Maintain a library of reusable program structures, slide assets, and case study inserts; flag gaps in the existing content library proactively.

4. Research & Market Intelligence

•   Track trends across the AI / GenAI / LLM ecosystem and Data Engineering & Analytics — translate findings into usable inputs for outreach, pitching, and offering design.

•   Identify new solution opportunities and product ideas based on market signals, customer asks, and competitor moves.

•   Benchmark StackRoute's offerings against competitors; surface gaps and differentiation angles for Senior SMEs and Practice Leads to act on.

5. Internal Collaboration

•   Work fluidly with Delivery, Sales, and external SMEs to ensure solutions designed on paper actually work in delivery — surface feasibility risks early, not late.

•   Coordinate inputs across Practice teams during pursuit cycles; hand off to delivery with documentation that captures customer commitments and success metrics.

Must Have Technical & Functional Skills

•   Good understanding of terminologies in Data Engineering (ETL, pipelines, data lakes), Data Analytics & BI concepts, and Machine Learning fundamentals, AI tools ( not technical expertise but L1-L2 knowledge should be present from application standpoint).

•   Awareness of GenAI / LLM vocabulary — prompt engineering, RAG, APIs — with enough depth to hold a credible first conversation with a technical stakeholder.

•   Strong PowerPoint skills (client-ready decks), Excel for effort estimation and costing basics, and structured documentation — proposals, SoWs, one-pagers.

•   Strong problem-solving and structured thinking — breaks complex requirements into clear, communicable solutions.

•   Comfortable communicating with both technical and non-technical stakeholders; good storytelling and presentation instincts; understanding of L&D context is a plus.

Qualifications & Experience

Required:

•   5-15 years in the education products, or in solutioning, pre-sales, or consulting roles with exposure of 3-5 years in Data/AI/Analytics.

•   Bachelor's or Master's in Computer Science, Data Science, Engineering, or a related discipline.

Nice to Have competences:

•   Prior pre-sales, proposal writing, or design development experience.

•   Certifications in cloud, data, or AI platforms (AWS, Azure, GCP, or model-provider certifications).

Core Competencies

·      Structured Thinking: Organises ambiguous client and technical inputs into logical, buyer-relevant narratives. Builds proposals that flow from problem to solution.

·      Solution Articulation: Translates Data & AI capabilities into crisp, persona-specific stories. Adapts the pitch for a CTO, L&D Head, or BU Head without losing substance.

·      Research & Synthesis: Gathers and distils large volumes of information into sharp, usable outputs. Knows what to include and what to leave out.

·      Written Communication: Writes a tight brief, a clean slide, and a clear email. Adapts register from internal working notes to buyer-facing collateral.

·      Curiosity & Learning Agility: Picks up new tools, concepts, and sectors quickly. Tracks AI / GenAI shifts proactively rather than waiting to be told what to read.

·      Bias for Action: Ships a useful 10-slide deck on time rather than a polished 20-slide deck that's late. Comfortable with iteration over perfection.

Job Description:

Experience: 10+ Years

Job Summary

We are looking for an experienced Azure Fabric Data Architect to lead the design and implementation of an enterprise data platform on Microsoft Fabric. The role involves architecting scalable data solutions, defining data governance, and enabling AI-driven analytics for a global financial services client.

Key Responsibilities

• Design end-to-end data architecture using Microsoft Fabric.
• Build enterprise Lakehouse, Data Warehouse, and OneLake solutions.
• Define data ingestion, ETL/ELT, governance, security, and performance strategies.
• Lead architecture for AI-powered analytics, AI Agents, and enterprise chatbots using Azure AI services.
• Work with business stakeholders to translate requirements into technical solutions.
• Mentor engineering teams and provide technical leadership.

Required Skills

• Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, OneLake)
• Azure Data Engineering
• Power BI
• Azure AI Services / Azure OpenAI
• Data Architecture & Data Modeling
• SQL, Python
• Azure DevOps, CI/CD
• Strong stakeholder management and solution design experience
• 
  

Preferred: Experience in Capital Markets or Financial Services and Microsoft Azure/Fabric certifications.

NOTE: One technical round is mandatory to be taken F2F from office.

10+ years of experience in Data Architecture, Data Engineering, or Data Platforms

• Strong expertise in IBM DB2 / On-Prem Relational Databases

• Strong expertise in PostgreSQL

• Hands-on experience with the Azure Data Ecosystem, including:

▪ Azure Data Factory (ADF)

▪ Azure Data Lake Storage Gen2 (ADLS Gen2)

▪ Azure Databricks / Synapse Analytics

▪ Azure Event Hub / Service Bus

▪ Azure Functions

Job Description

We are looking for an experienced Azure Synapse Data Engineer with strong hands-on expertise in Azure data engineering, data warehousing, ETL/ELT, and SQL performance optimization.

Key Responsibilities

• Design, develop, and optimize solutions using Azure Synapse Analytics.
• Build and maintain data integration pipelines using Azure Data Factory (ADF) and Synapse Pipelines.
• Design and implement scalable Azure Data Lake Storage Gen2 (ADLS Gen2) architectures.
• Develop robust and high-performance ETL/ELT frameworks for enterprise data platforms.
• Monitor and troubleshoot large-scale data ingestion, transformation, and processing workloads.
• Identify and resolve performance bottlenecks across data movement and transformation processes.
• Ensure data quality, availability, reliability, and consistency across analytics platforms.
• Perform advanced SQL query analysis and optimization.
• Analyze execution plans and optimize complex analytical workloads.
• Configure and tune Synapse Dedicated SQL Pools.
• Design efficient partitioning strategies for large datasets.
• Optimize indexing, statistics, and workload distribution to improve query performance.

Mandatory Skills

• Azure Synapse Analytics
• Azure Data Factory (ADF)
• Synapse Pipelines
• ADLS Gen2
• ETL/ELT
• Strong SQL
• Synapse Dedicated SQL Pool
• SQL query/execution plan optimization
• Partitioning, indexing, and statistics
• Azure data warehouse / data lake architecture
• Performance tuning and troubleshooting

Ideal Candidate

A strong Azure Data Engineer with hands-on experience in Synapse + ADF + ADLS Gen2 + Advanced SQL + Dedicated SQL Pool performance tuning.

Hiring : Senior Databricks AI Architect

Exp : 15 - 18 yrs

Work Location : Pune WFO

Skills :

10 +years of experience in Data Engineering, Data Architecture, Analytics, or Software Engineering.

Minimum 5 years of hands-on experience with Databricks (Mandatory).

Strong expertise in designing and implementing enterprise-scale data platforms on Databricks.

Hands-on experience with AI-powered engineering tools such as Databricks Genie, Cursor, GitHub Copilot, or similar AI platforms.

Strong proficiency in Python, SQL, Spark, Delta Lake, and Databricks notebooks.

Excellent communication, stakeholder management

Solution Architect – AZURE Data Engineering

Job Overview

We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.

Key Responsibilities

• Design and implement scalable data architecture and solutions.
• Develop and manage Data Warehouse and Data Lake architectures.
• Design data platforms using Medallion Architecture.
• Lead Data Engineering and ETL activities.
• Work with Azure Synapse Analytics for data processing and analytics.
• Develop data solutions using PySpark / Apache Spark.
• Define and implement data validation and data quality processes.
• Collaborate with business, data, and technology teams to deliver effective data solutions.

Required Skills

• Strong experience in Solution Architecture / Data Architecture.
• Strong knowledge of Data Warehouse and Data Lake architecture.
• Good understanding of Medallion Architecture.
• Strong experience in Data Engineering and ETL.
• Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
• Strong knowledge of PySpark / Apache Spark.
• Experience with Data Validation and Data Quality.
• Good communication and stakeholder management skills.
• 
  

Experience

8+ Years

Job Summary/ Job Opportunity:

This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde

Key Objectives and Major Responsibilities:

• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team

Key Capabilities and Competencies:

Knowledge, Skills, Qualification and Experience

• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies. 

About E2M:

E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, eCommerce, SEO, AI SEO, PPC, AI automation, and content writing .Founded on strong business ethics, we are an equal opportunity organization powered by 300+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together .If you’re someone who dreams big and has the gumption to make them come true, E2M has a place for you.

Role Overview:

We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.

Key Responsibilities:

• Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.
• Assess client requirements and prepare solution strategies using AI tools and methodologies.
• Work with internal teams to design, propose, and help execute AI-powered solutions.
• Provide AI-based recommendations that align with the client’s business objectives.
• Communicate technical possibilities in a business-friendly manner to decision-makers.
• Take ownership of the client journey from discovery to implementation and support.
• Stay updated with AI trends, tools, and real-world use cases that can benefit clients.

Required Skills & Qualifications:

• Minimum 2+ Years of hands on experience into Custom AI Development.
• Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency.
• Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologies).
•  Some hands-on experience in AI projects – either through execution, coordination, or implementation.
• Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders.
•  Strong problem-solving mind set with the ability to translate business needs into AI opportunities.
• Flexible to work with international clients, especially in the US time zone as needed.