Technical Content Writer

Position: Sales Manager

Location: Panipat

Experience required: Minimum 3 years (B2B Sales) – Field sales

Salary Range: 4.80 LPA

Working Days: 5.5 days working (First 2 Saturdays and all Sundays are off)

Job Type: Full Time

Requirement: Bike and Laptop (Mandatory)

Key Responsibilities

 Drive B2B sales growth and achieve revenue targets in the industrial segment.

 Utilize platform to generate leads and expand business opportunities.

 Develop and implement effective sales strategies for market penetration and client

acquisition.

 Build, mentor, and manage a sales team to enhance performance and productivity.

 Identify new business opportunities and maintain strong relationships with existing clients.

 Conduct market research to understand industry trends and competitor activities.

 Coordinate with internal departments to ensure timely delivery and customer satisfaction.

 Travel to meet clients, attend meetings, and explore new business prospects.

Eligibility Criteria

 Minimum 3 years of experience in B2B sales.

 Good knowledge and practical exposure to Alibaba.com.

 Proven experience in team handling and team building.

 Strong understanding of industrial products and market dynamics.

Role: Senior Data Engineer (Azure)

Experience: 5+ Years

Location: Anywhere in india

Work Mode: Remote

Notice Period - Immediate joiners or Serving notice period

𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬:

• Data processing on Azure using ADF, Streaming Analytics, Event Hubs, Azure Databricks, Data Migration Services, and Data Pipelines
• Provisioning, configuring, and developing Azure solutions (ADB, ADF, ADW, etc.)
• Designing and implementing scalable data models and migration strategies
• Working on distributed big data batch or streaming pipelines (Kafka or similar)
• Developing data integration & transformation solutions for structured and unstructured data
• Collaborating with cross-functional teams for performance tuning and optimization
• Monitoring data workflows and ensuring compliance with governance and quality standards
• Driving continuous improvement through automation and DevOps practices
• 
  

𝐌𝐚𝐧𝐝𝐚𝐭𝐨𝐫𝐲 𝐒𝐤𝐢𝐥𝐥𝐬 & 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞:

• 5–10 years of experience as a Data Engineer
• Strong proficiency in Azure Databricks, PySpark, Python, SQL, and Azure Data Factory
• Experience in Data Modelling, Data Migration, and Data Warehousing
• Good understanding of database structure principles and schema design
• Hands-on experience with MS SQL Server, Oracle, or similar RDBMS platforms
• Experience with DevOps tools (Azure DevOps, Jenkins, Airflow, Azure Monitor) — good to have
• Knowledge of distributed data processing and real-time streaming (Kafka/Event Hub)
• Familiarity with visualization tools like Power BI or Tableau
• Strong analytical, problem-solving, and debugging skills
• Self-motivated, detail-oriented, and capable of managing priorities effectively

Review Criteria:

• Strong Dremio / Lakehouse Data Architect profile
• 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
• Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
• Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
• Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
• Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
• Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
• Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
• Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies

Preferred:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments

Role & Responsibilities:

You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

Ideal Candidate:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

Preferred:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.

About the Role

We are seeking a highly skilled Senior AI/ML Engineer to join our dynamic team. The ideal candidate will have extensive experience in designing, building, and deploying machine learning models and AI solutions to solve real-world business challenges. You will collaborate with cross-functional teams to create and integrate AI/ML models into end-to-end applications, ensuring models are accessible through APIs or product interfaces for real-time usage.

Responsibilities

• Lead the design, development, and deployment of machine learning models for various use cases such as recommendation systems, computer vision, natural language processing (NLP), and predictive analytics.

• Work with large datasets to build, train, and optimize models using techniques such as classification, regression, clustering, and neural networks.

• Fine-tune pre-trained models and develop custom models based on specific business needs.

• Collaborate with data engineers to build scalable data pipelines and ensure the smooth integration of models into production.

• Collaborate with frontend/backend engineers to build AI-driven features into products or platforms.

• Build proof-of-concept or production-grade AI applications and tools with intuitive UIs or workflows.

• Ensure scalability and performance of deployed AI solutions within the full application stack.

• Implement model monitoring and maintenance strategies to ensure performance, accuracy, and continuous improvement of deployed models.

• Design and implement APIs or services that expose machine learning models to frontend or other systems

• Utilize cloud platforms (AWS, GCP, Azure) to deploy, manage, and scale AI/ML solutions.

• Stay up-to-date with the latest advancements in AI/ML research, and apply innovative techniques to improve existing systems.

• Communicate effectively with stakeholders to understand business requirements and translate them into AI/ML-driven solutions.

• Document processes, methodologies, and results for future reference and reproducibility.

Required Skills & Qualifications

• Experience: 3-5+ years of experience in AI/ML engineering roles, with a proven track record of successfully delivering machine learning projects.

• AI/ML Expertise: Strong knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and AI techniques, including NLP, computer vision, and recommendation systems.

• Programming Languages: Proficient in Python and relevant ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.

• Data Manipulation: Experience with data manipulation libraries such as Pandas, NumPy, and SQL for managing and processing large datasets.

• Model Development: Expertise in building, training, deploying, and fine-tuning machine learning models in production environments.

• Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for the deployment and scaling of AI/ML models.

• MLOps: Knowledge of MLOps practices for model versioning, automation, and monitoring.

• Data Preprocessing: Proficient in data cleaning, feature engineering, and preparing datasets for model training.

• Strong experience building and deploying end-to-end AI-powered applications— not just models but full system integration.

• Hands-on experience with Flask, FastAPI, Django, or similar for building REST APIs for model serving.

• Understanding of system design and software architecture for integrating AI into production environments.

• Experience with frontend/backend integration (basic React/Next.js knowledge is a plus).

• Demonstrated projects where AI models were part of deployed user-facing applications.

• NLP & Computer Vision: Hands-on experience with natural language processing or computer vision projects.

• Big Data: Familiarity with big data tools and frameworks (e.g., Apache Spark, Hadoop) is an advantage.

• Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering practical AI/ML solutions.

Nice to Have

• Experience with deep learning architectures (CNNs, RNNs, GANs, etc.) and techniques.

• Knowledge of deployment strategies for AI models using APIs, Docker, or Kubernetes.

• Experience building full-stack applications powered by AI (e.g., chatbots, recommendation dashboards, AI assistants, etc.).

• Experience deploying AI/ML models in real-time environments using API gateways, microservices, or orchestration tools like Docker and Kubernetes.

• Solid understanding of statistics and probability.

• Experience working in Agile development environments.

What You'll Gain

• Be part of a forward-thinking team working on cutting-edge AI/ML technologies.

• Collaborate with a diverse, highly skilled team in a fast-paced environment.

• Opportunity to work on impactful projects with real-world applications.

• Competitive salary and career growth opportunities

Requirements:

• Previously help a DevOps Engineer or System Engineer role

• 4+ years of production Linux system admin experience in high traffic environment

• 1+ years of experience with Amazon AWS and related services (instances, ELB,

   EBS, S3, etc.) and abstractions on top of AWS.

• Strong understanding of network fundamentals, IP and related services (DNS, VPN, firewalls, etc.) and    

   security concerns.

• Experience in running Docker and Kubernetes clusters in production.

• Love automating mundane tasks and make developers life easy

• Must be able to code in, at a minimum, Python (or Ruby) and Bash.

• Non-trivial production experience with Saltstack and/or Puppet, Composer,Jenkins, GIT

• Agile software development best practices - continuous integration, releases,branches, etc.

• Experience with modern monitoring tools; capacity planning.

• Some experience with MySQL, PostgreSQL, ElasticSearch, Node.js, and PHP is a plus.

• Self-motivated, fast learner, detail-oriented, team player with a sense of humor

Experience in managing CI/CD using Jenkins.

• 7+ years of full-time work experience after completing an undergraduate degree
• At least 2+ years of experience in engineering management experience.
• Experience with AWS, GCP, and/or Azure technologies including serverless
• You know what high-quality code — and software engineering processes — look like and know how to foster an environment that creates them.
• Execution focused with an ability to navigate ambiguity.
• Ability to do both long-term thinking and short-term planning.
• Experience creating, delivering, and operating multi-tenanted, distributed systems at scale.
• Experience leading 5+ engineers is preferred.