Quantiphi

We are looking for a skilled Data Engineer / Data Warehouse Engineer to design, develop, and maintain scalable data pipelines and enterprise data warehouse solutions. The role involves close collaboration with business stakeholders and BI teams to deliver high-quality data for analytics and reporting.

Key Responsibilities

• Collaborate with business users and stakeholders to understand business processes and data requirements
• Design and implement dimensional data models, including fact and dimension tables
• Identify, design, and implement data transformation and cleansing logic
• Build and maintain scalable, reliable, and high-performance ETL/ELT pipelines
• Extract, transform, and load data from multiple source systems into the Enterprise Data Warehouse
• Develop conceptual, logical, and physical data models, including metadata, data lineage, and technical definitions
• Design, develop, and maintain ETL workflows and mappings using appropriate data load techniques
• Provide high-level design, research, and effort estimates for data integration initiatives
• Provide production support for ETL processes to ensure data availability and SLA adherence
• Analyze and resolve data pipeline and performance issues
• Partner with BI teams to design and develop reports and dashboards while ensuring data integrity and quality
• Translate business requirements into well-defined technical data specifications
• Work with data from ERP, CRM, HRIS, and other transactional systems for analytics and reporting
• Define and document BI usage through use cases, prototypes, testing, and deployment
• Support and enhance data governance and data quality processes
• Identify trends, patterns, anomalies, and data quality issues, and recommend improvements
• Train and support business users, IT analysts, and developers
• Lead and collaborate with teams spread across multiple locations

Required Skills & Qualifications

• Bachelor’s degree in Computer Science or a related field, or equivalent work experience
• 3+ years of experience in Data Warehousing, Data Engineering, or Data Integration
• Strong expertise in data warehousing concepts, tools, and best practices
• Excellent SQL skills
• Strong knowledge of relational databases such as SQL Server, PostgreSQL, and MySQL
• Hands-on experience with Google Cloud Platform (GCP) services, including:

1. BigQuery
2. Cloud SQL
3. Cloud Composer (Airflow)
4. Dataflow
5. Dataproc
6. Cloud Functions
7. Google Cloud Storage (GCS)

• Experience with Informatica PowerExchange for Mainframe, Salesforce, and modern data sources
• Strong experience integrating data using APIs, XML, JSON, and similar formats
• In-depth understanding of OLAP, ETL frameworks, Data Warehousing, and Data Lakes
• Solid understanding of SDLC, Agile, and Scrum methodologies
• Strong problem-solving, multitasking, and organizational skills
• Experience handling large-scale datasets and database design
• Strong verbal and written communication skills
• Experience leading teams across multiple locations

Good to Have

• Experience with SSRS and SSIS
• Exposure to AWS and/or Azure cloud platforms
• Experience working with enterprise BI and analytics tools

Why Join Us

• Opportunity to work on large-scale, enterprise data platforms
• Exposure to modern cloud-native data engineering technologies
• Collaborative environment with strong stakeholder interaction
• Career growth and leadership opportunities

We are seeking a skilled and passionate ML Engineer with 3+ years of experience to join our team. The ideal candidate will be instrumental in developing, deploying, and maintaining machine learning models, with a strong focus on MLOps practices.

This role requires hands-on experience with Azure cloud services, Databricks, and MLflow to build robust and scalable ML solutions.

Responsibilities

• Design, develop, and implement machine learning models and algorithms to solve complex business problems.
• Collaborate with data scientists to transition models from research and development into production-ready systems.
• Build and maintain scalable data pipelines for ML model training and inference using Databricks.
• Implement and manage the ML model lifecycle using MLflow, including experiment tracking, model versioning, and model registry.
• Deploy and manage ML models in production environments on Azure, leveraging services such as:
• Azure Machine Learning
• Azure Kubernetes Service (AKS)
• Azure Functions
• Support MLOps workloads by automating model training, evaluation, deployment, and monitoring processes.
• Ensure the reliability, performance, and scalability of ML systems in production.
• Monitor model performance, detect model drift, and implement retraining strategies.
• Collaborate with DevOps and Data Engineering teams to integrate ML solutions into existing infrastructure and CI/CD pipelines.
• Document model architecture, data flows, and operational procedures.

Qualifications

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related quantitative field.

Experience

• Minimum 3+ years of professional experience as an ML Engineer or in a similar role.

Required Skills

• Strong proficiency in Python for data manipulation, machine learning, and scripting.
• Hands-on experience with machine learning frameworks, such as:
• Scikit-learn
• TensorFlow
• PyTorch
• Keras
• Demonstrated experience with MLflow for:
• Experiment tracking
• Model management
• Model deployment
• Proven experience working with Microsoft Azure cloud services, specifically:
• Azure Machine Learning
• Azure Databricks
• Related compute and storage services
• Solid experience with Databricks for:
• Data processing
• ETL pipelines
• ML model development
• Strong understanding of MLOps principles and practices, including:
• CI/CD for ML
• Model versioning
• Model monitoring
• Model retraining
• Experience with containerization and orchestration technologies, including:
• Docker
• Kubernetes (especially AKS)
• Familiarity with SQL and data warehousing concepts.
• Experience working with large datasets and distributed computing frameworks.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.

Nice-to-Have Skills

• Experience with other cloud platforms (AWS or GCP).
• Knowledge of big data technologies such as Apache Spark.
• Experience with Azure DevOps for CI/CD pipelines.
• Familiarity with real-time inference patterns and streaming data.
• Understanding of Responsible AI principles, including fairness, explainability, and privacy.

Certifications (Preferred)

• Microsoft Certified: Azure AI Engineer Associate
• Databricks Certified Machine Learning Associate (or higher) 

Role & Responsibilities

• Develop and deliver automation software to build and improve platform functionality
• Ensure reliability, availability, and manageability of applications and cloud platforms
• Champion adoption of Infrastructure as Code (IaC) practices
• Design and build self-service, self-healing, monitoring, and alerting platforms
• Automate development and testing workflows through CI/CD pipelines (Git, Jenkins, SonarQube, Artifactory, Docker containers)
• Build and manage container hosting platforms using Kubernetes

Requirements

• Strong experience deploying and maintaining GCP cloud infrastructure
• Well-versed in service-oriented and cloud-based architecture design patterns
• Knowledge of cloud services including compute, storage, networking, messaging, and automation tools (e.g., CloudFormation/Terraform equivalents)
• Experience with relational and NoSQL databases (Postgres, Cassandra)
• Hands-on experience with automation/configuration tools (Puppet, Chef, Ansible, Terraform)

Additional Skills

• Strong Linux system administration and troubleshooting skills
• Programming/scripting exposure (Bash, Python, Core Java, or Scala)
• CI/CD pipeline experience (Jenkins, Git, Maven, etc.)
• Experience integrating solutions in multi-region environments
• Familiarity with Agile/Scrum/DevOps methodologies

Responsible for developing, enhancing, modifying, and maintaining chatbot applications in the Global Markets environment. The role involves designing, coding, testing, debugging, and documenting conversational AI solutions, along with supporting activities aligned to the corporate systems architecture.

You will work closely with business partners to understand requirements, analyze data, and deliver optimal, market-ready conversational AI and automation solutions.

Key Responsibilities

• Design, develop, test, debug, and maintain chatbot and virtual agent applications
• Collaborate with business stakeholders to define and translate requirements into technical solutions
• Analyze large volumes of conversational data to improve chatbot accuracy and performance
• Develop automation workflows for data handling and refinement
• Train and optimize chatbots using historical chat logs and user-generated content
• Ensure solutions align with enterprise architecture and best practices
• Document solutions, workflows, and technical designs clearly

Required Skills

• Hands-on experience in developing virtual agents (chatbots/voicebots) and Natural Language Processing (NLP)
• Experience with one or more AI/NLP platforms such as:
• Dialogflow, Amazon Lex, Alexa, Rasa, LUIS, Kore.AI
• Microsoft Bot Framework, IBM Watson, Wit.ai, Salesforce Einstein, Converse.ai
• Strong programming knowledge in Python, JavaScript, or Node.js
• Experience training chatbots using historical conversations or large-scale text datasets
• Practical knowledge of:
• Formal syntax and semantics
• Corpus analysis
• Dialogue management
• Strong written communication skills
• Strong problem-solving ability and willingness to learn emerging technologies

Nice-to-Have Skills

• Understanding of conversational UI and voice-based processing (Text-to-Speech, Speech-to-Text)
• Experience building voice apps for Amazon Alexa or Google Home
• Experience with Test-Driven Development (TDD) and Agile methodologies
• Ability to design and implement end-to-end pipelines for AI-based conversational applications
• Experience in text mining, hypothesis generation, and historical data analysis
• Strong knowledge of regular expressions for data cleaning and preprocessing
• Understanding of API integrations, SSO, and token-based authentication
• Experience writing unit test cases as per project standards
• Knowledge of HTTP, REST APIs, sockets, and web services
• Ability to perform keyword and topic extraction from chat logs
• Experience training and tuning topic modeling algorithms such as LDA and NMF
• Understanding of classical Machine Learning algorithms and appropriate evaluation metrics
• Experience with NLP frameworks such as NLTK and spaCy

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Some company highlights:

• Quantiphi has seen 2.5x growth YoY since its inception in 2013.
• Winner of the "Machine Learning Partner of the Year" award from Google for two consecutive years - 2017 and 2018.
• Winner of the "Social Impact Partner of the Year" award from Google for 2019.
• Headquartered in Boston, with 700+ data science professionals across different offices.

For more details, visit: our http://www.quantiphi.com/">Website or our https://www.linkedin.com/company/quantiphi/">LinkedIn Page

Job Description

Role:                                 Associate Tech Architect / Tech Architect – ReactJS +Python+AWS

Experience Level:           7-13 Years

Work location:                Mumbai & Bangalore

We are looking for an experienced full stack developer( ReactJS and Python ) who can help create dynamic software applications for our clients with their skill set. In this role, you will be responsible for gathering requirements from clients and accordingly write and test scalable code, and develop front end and back-end components.

Technologies worked on:

ReactJS, Python, AWS

Requirement Description:

• Full Stack developer with experience in ReactJS, Python, API Gateway, Fargate and ECS
• Well-experienced in working with tools like Git, Maven, JFrog
• Should have a solid understanding of object-oriented programming (OOP)
• Well-experienced to perform Unit Testing and Integration Testing and have good experience in Agile based development approach
• Expertise in developing enterprise-level web applications and REST and SOAP APIs using MicroServices, with demonstrable production-scale experience
• Demonstrate strong design and programming skills using JSON, Web Services, XML, XSLT, PL/SQL in Unix and Windows environments
• Strong background working with Linux/UNIX environments and strong Shell scripting experience
• Working knowledge with SQL or  No SQL databases
• Understand Architecture Requirements and ensure effective design, development, validation, and support activities
• Understanding of core AWS services, uses, and basic AWS architecture best practices
• Proficiency in developing, deploying, and debugging cloud-based applications using AWS
• Ability to use the AWS service APIs, AWS CLI, and SDKs to write applications
• Ability to identify key features of AWS services
• Identify bottlenecks and bugs, and recommend solutions by comparing the advantages and disadvantages of custom development
• Should contribute to team meetings, troubleshooting development and production problems across multiple environments and operating platforms
• Execute strong collaboration and communication skills within distributed project teams
• Continuously discover, evaluate, and implement new technologies to maximize development efficiency