SEO Executive

Review Criteria

• Strong Data / ETL Test Engineer
• 5+ years of overall experience in Testing/QA
• 3+ years of hands-on end-to-end data testing/ETL testing experience, covering data extraction, transformation, loading validation, reconciliation, working across BI / Analytics / Data Warehouse / e-Governance platforms
• Must have strong understanding and hands-on exposure to Data Warehouse concepts and processes, including fact & dimension tables, data models, data flows, aggregations, and historical data handling.
• Must have experience in Data Migration Testing, including validation of completeness, correctness, reconciliation, and post-migration verification from legacy platforms to upgraded/cloud-based data platforms.
• Must have independently handled test strategy, test planning, test case design, execution, defect management, and regression cycles for ETL and BI testing
• Hands-on experience with ETL tools and SQL-based data validation is mandatory (Working knowledge or hands-on exposure to Redshift and/or Qlik will be considered sufficient)
• Must hold a Bachelor’s degree B.E./B.Tech else should have master's in M.Tech/MCA/M.Sc/MS
• Must demonstrate strong verbal and written communication skills, with the ability to work closely with business stakeholders, data teams, and QA leadership
• Mandatory Location: Candidate must be based within Delhi NCR (100 km radius)

Preferred

• Relevant certifications such as ISTQB or Data Analytics / BI certifications (Power BI, Snowflake, AWS, etc.)

Job Specific Criteria

• CV Attachment is mandatory
• Do you have experience working on Government projects/companies, mention brief about project?
• Do you have experience working on enterprise projects/companies, mention brief about project?
• Please mention the names of 2 key projects you have worked on related to Data Warehouse / ETL / BI testing?
• Do you hold any ISTQB or Data / BI certifications (Power BI, Snowflake, AWS, etc.)?
• Do you have exposure to BI tools such as Qlik?
• Are you willing to relocate to Delhi and why (if not from Delhi)?
• Are you available for a face-to-face round?

Role & Responsibilities

• 5 years’ experience in Data Testing across BI Analytics platforms with at least 2 largescale enterprise Data Warehouse Analytics eGovernance programs
• Proficiency in ETL Data Warehouse and BI report dashboard validation including test planning data reconciliation acceptance criteria definition defect triage and regression cycle management for BI landscapes
• Proficient in analyzing business requirements and data mapping specifications BRDs Data Models Source to Target Mappings User Stories Reports Dashboards to define comprehensive test scenarios and test cases
• Ability to review high level and low-level data models ETL workflows API specifications and business logic implementations to design test strategies ensuring accuracy consistency and performance of data pipelines
• Ability to test and validate the migrated data from old platform to an upgraded platform and ensure the completeness and correctness of migration
• Experience of conducting test of migrated data and defining test scenarios and test cases for the same
• Experience with BI tools like Qlik ETL platforms Data Lake platforms Redshift to support end to end validation
• Exposure to Data Quality Metadata Management and Data Governance frameworks ensuring KPIs metrics and dashboards align with business expectations

Ideal Candidate

• 5 years’ experience in Data Testing across BI Analytics platforms with at least 2 largescale enterprise Data Warehouse Analytics eGovernance programs
• Proficiency in ETL Data Warehouse and BI report dashboard validation including test planning data reconciliation acceptance criteria definition defect triage and regression cycle management for BI landscapes
• Proficient in analyzing business requirements and data mapping specifications BRDs Data Models Source to Target Mappings User Stories Reports Dashboards to define comprehensive test scenarios and test cases
• Ability to review high level and low-level data models ETL workflows API specifications and business logic implementations to design test strategies ensuring accuracy consistency and performance of data pipelines
• Ability to test and validate the migrated data from old platform to an upgraded platform and ensure the completeness and correctness of migration
• Experience of conducting test of migrated data and defining test scenarios and test cases for the same
• Experience with BI tools like Qlik ETL platforms Data Lake platforms Redshift to support end to end validation
• Exposure to Data Quality Metadata Management and Data Governance frameworks ensuring KPIs metrics and dashboards align with business expectations

Job Details

- Job Title: Enterprise Sales Manager (B2B SaaS)

- Industry: Software Technology Company

- Experience Required: 2-10 years

- Working Days: 5 days/week

- Job Location: Mumbai

- CTC Range: Best in Industry

Review Criteria

• Strong enterprise sales executive profile
• 2+ years of selling B2B SaaS.
• Must have 2+ of experience of selling to enterprise clients OR to manufacturing industry OR selling FinTech product, SAP Product sales/Finance ERP solutions (like invoice processing, vendor management, Source to pay, Compliance solutions).
• Must have experience in end-to-end sales from lead generation, prospecting, demos, proposal building, negotiation, and deal closure
• Must have stable career history — no frequent job hopping
• Final round is F2F (client will handle the travel)

Role & Responsibilities

We are looking for a dynamic and results-driven Enterprise Sales Manager to drive our sales strategy and expand our market presence. This role demands a strong understanding of SAP/Finance ERP solutions, excellent communication skills, and a proven track record in IT/software sales.

Key Responsibilities:

• Sales Strategy Development: Develop and execute sales plans to achieve company revenue targets in the SAP/ERP domain.
• Client Acquisition: Identify, engage, and convert prospective clients by demonstrating the value of our SAP/ERP solutions.
• Relationship Management: Build and maintain long-term relationships with clients, ensuring high levels of satisfaction and retention.
• Market Analysis: Stay updated on industry trends, competitor activities, and market demands to identify growth opportunities.
• Proposal & Presentation: Prepare and deliver compelling proposals, presentations, and demos tailored to client needs.
• Collaboration: Work closely with technical and consulting teams to ensure seamless delivery of solutions and services.

Ideal Candidate

• Experience: Minimum 2 years in sales, with a strong focus on SAP Product sales/Finance ERP solutions
• Industry Preference: Candidates with prior experience in handling manufacturing industry clients will be given preference.
• Educational Qualification: Bachelor’s degree in Business, IT, or a related field. An MBA is an added advantage.

Skills:

• Proven ability to meet and exceed sales targets.
• Excellent communication, negotiation, and presentation skills.
• Understanding of SAP/ERP systems and their applications in business processes.
• Strong client relationship management abilities.
• Track record of success managing large enterprise accounts
• Track record of consistently over-achieving quota (top 10% in your company)
• Strong interpersonal and presentation skills
• Exceptional verbal and written communication skills
• Ability to travel to prospects and customers if required
• Good organizer with the ability to prioritize and multitask
• Proven ability to manage multiple concurrent sales cycles.

🤖 Data Scientist – Frontier AI for Data Platforms & Distributed Systems (4–8 Years)

Experience: 4–8 Years

Location: Bengaluru (On-site / Hybrid)

Company: Publicly Listed, Global Product Platform

🧠 About the Mission

We are building a Top 1% AI-Native Engineering & Data Organization — from first principles.

This is not incremental improvement.

This is a full-stack transformation of a large-scale enterprise into an AI-native data platform company.

We are re-architecting:

• Legacy systems → AI-native architectures
• Static pipelines → autonomous, self-healing systems
• Data platforms → intelligent, learning systems
• Software workflows → agentic execution layers

This is the kind of shift you would expect from companies like Google or Microsoft —

Except here, you will build it from day zero and scale it globally.

🧠 The Opportunity: This role sits at the intersection of three high-impact domains:

1. Frontier AI Systems: Large Language Models (LLMs), Small Language Models (SLMs), and Agentic AI

2. Data Platforms: Warehouses, Lakehouses, Streaming Systems, Query Engines

3. Distributed Systems: High-throughput, low-latency, multi-region infrastructure

We are building systems where:

• Data platforms optimize themselves using ML/LLMs
• Pipelines are autonomous, self-healing, and adaptive
• Queries are generated, optimized, and executed intelligently
• Infrastructure learns from usage and evolves continuously

This is: AI as the control plane for data infrastructure

🧩 What You’ll Work On

You will design and build AI-native systems deeply embedded inside data infrastructure.

1. AI-Native Data Platforms

• Build LLM-powered interfaces:
• Natural language → SQL / pipelines / transformations
• Design semantic data layers:
• Embeddings, vector search, knowledge graphs
• Develop AI copilots:
• For data engineers, analysts, and platform users

2. Autonomous Data Pipelines

• Build self-healing ETL/ELT systems using AI agents
• Create pipelines that:
• Detect anomalies in real time
• Automatically debug failures
• Dynamically optimize transformations

3. Intelligent Query & Compute Optimization

• Apply ML/LLMs to:
• Query planning and execution
• Cost-based optimization using learned models
• Workload prediction and scheduling
• Build systems that:
• Learn from query patterns
• Continuously improve performance and cost efficiency

4. Distributed Data + AI Infrastructure

• Architect systems operating at:
• Billions of events per day
• Petabyte-scale data
• Work with:
• Distributed compute engines (Spark / Flink / Ray class systems)
• Streaming systems (Kafka-class infra)
• Vector databases and hybrid retrieval systems

5. Learning Systems & Feedback Loops

• Build closed-loop AI systems:
• Execution → feedback → model updates
• Develop:
• Continual learning pipelines
• Online learning systems for infra optimization
• Experimentation frameworks (A/B, bandits, eval pipelines)

6. LLM & Agentic Systems (Infra-Aware)

• Build agents that understand data systems
• Enable:
• Autonomous pipeline debugging
• Root cause analysis for infra failures
• Intelligent orchestration of data workflows

🧠 What We’re Looking For

Core Foundations

• Strong grounding in:
• Machine Learning, Deep Learning, NLP
• Statistics, optimization, probabilistic systems
• Distributed systems fundamentals
• Deep understanding of:
• Transformer architectures
• Modern LLM ecosystems

Hands-On Expertise

• Experience building:
• LLM / GenAI systems (RAG, fine-tuning, embeddings)
• Data platforms (warehouse, lake, lakehouse architectures)
• Distributed pipelines and compute systems
• Strong programming skills:
• Python (ML/AI stack)
• SQL (deep understanding — query planning, optimization mindset)

Systems Thinking (Critical)

You think in systems, not components.

• Built or worked on:
• Large-scale data pipelines
• High-throughput distributed systems
• Low-latency, high-concurrency architectures
• Understand:
• Query optimization and execution
• Data partitioning, indexing, caching
• Trade-offs in distributed systems

🔥 What Sets You Apart (Top 1%)

• Built AI-powered data platforms or infra systems in production
• Designed or contributed to:
• Query engines / optimizers
• Data observability / lineage systems
• AI-driven infra or AIOps platforms
• Experience with:
• Multi-modal AI (logs, metrics, traces, text)
• Agentic AI systems
• Autonomous infrastructure
• Worked on systems at scale comparable to:
• Google (BigQuery-like systems)
• Meta (real-time analytics infra)
• Snowflake / Databricks (lakehouse architectures)

🧬 Ideal Background (Not Mandatory)

We often see strong candidates from:

• Data infrastructure or platform engineering teams
• AI-first startups or research-driven environments
• High-scale product companies

Experience building:

• Internal platforms used by 1000s of engineers
• Systems serving millions of users / high throughput workloads
• Multi-region, distributed cloud systems

🧠 The Kind of Problems You’ll Solve

• Can LLMs replace traditional query optimizers?
• How do we build self-healing data pipelines at scale?
• Can data systems learn from every query and improve automatically?
• How do we embed reasoning and planning into infrastructure layers?
• What does a fully autonomous data platform look like?

Background: We Commonly See (But Not Limited To)

Our team often includes engineers from top-tier institutions and strong research or product backgrounds, including:

• Leading engineering schools in India and globally
• Engineers with experience in top product companies, AI startups, or research-driven environments
• That said, we care far more about demonstrated ability, depth, and impact than pedigree alone.

Key Responsibilities

• Design, develop, and maintain mobile automation frameworks using Appium
• Automate native, hybrid, and mobile web applications (Android & iOS)
• Write, execute, and maintain automated test scripts
• Perform regression, smoke, and sanity testing
• Integrate automation scripts into CI/CD pipelines
• Analyze test results and report defects using bug tracking tools
• Collaborate with developers, product owners, and QA team
• Participate in test planning and test case review

Note : Face 2 Face interview is mandatory on weekdays

Responsibilities & Duties: 

Making Calls to Customers, Maintaining the Database

Lead Verification

Handle client queries/escalations.

Maintain relations with the existing clients and ask to upgrade their packages or renewals

Required Experience, Skills, and Qualifications

Experience: Fresher

Skills: Proficient Written & Verbal Communication Skills in English

Qualifications: Any Graduate

Job Description for Java:

• Experience in JAVA programming and application development using Spring MVC, Spring Boot, Spring Security, Hibernate and Microservices

• Experience in building products with Full stack technologies, with excellent understanding of computer science fundamentals, data structures, algorithms, OOPs and OOA/D

• Experience in MySQL, Mongo dB (or other NOSQL db’s), REST, Web Sockets, JavaScript, Ajax

• Experience with GO a plus

• Experience with one of JavaScript Frameworks (React, Angular, Vue etc.)

• Experience in Rest API development using Spring MVC or Spring Boot

• Able to define, design, implement complex, and scalable systems

• Good team player and communication skills

• Experience with agile development methodologies with Test Driven Development (TDD)

• Experience with Jenkins Setup CI/CD (Continuous Integration / Continuous delivery)

Job Description

• Identifies business opportunities by identifying prospects and evaluating their position in the industry; researching and analyzing sales options.
• Sells products by establishing contact and developing relationships with prospects; recommending solutions.
• Maintains relationships with clients by providing support, information, and guidance; researching and recommending new opportunities; recommending profit and service improvements.
• Identifies product improvements or new products by remaining current on industry trends, market activities, and competitors.
• Prepares reports by collecting, analyzing, and summarizing information.
• Maintains quality service by establishing and enforcing organization standards.

• Contributes to team effort by accomplishing related results as needed.

• Team Handling.

Skills Required:

• Strong communication
• Strong marketing skills including negotiation and convincing
• Good oral/written/interpersonal/presentation skills.
• Possesses an energetic, outgoing and friendly demeanor.