Business Development Executive

Role - Dynamics 365 Data Migration Engineer/Developer

Experience level: 5+ years

Location: Remote

Prior experience in Dynamics 365 data migration projects.

knowledge of SSIS, Azure Fabric, and Azure Data Factory.

Good understanding of Dataverse data structure and integration patterns.

Proficiency in SQL for data extraction and transformation.

Experience in preparing data mapping and migration documentation.

Collaborate with functional teams for data validation and reconciliation.

Prepare data mapping documents and ensure accurate transformation

Strong Technical Project Manager / Program Manager / Implementation manager profile

Mandatory (Experience 1) – Must have 5+ years in Delivery manager/ Technical Implementation Manager/ Technical Project Management / Technical Program Management Implementation Engineer with a B2B SaaS OR Tier1 service companies (preferably with enterprise client)

Mandatory (Experience 2) – Must have direct experience leading end-to-end software/product/tech project delivery

Mandatory (Experience 3) – Must have External / Client project implementation experience (Don't want internal project manager)

Mandatory (Core Skills) – Strong communication, stakeholder management, and executive-level reporting capability

Mandatory (Company) -B2B SaaS OR Tier1 Service companies (Service companies like Accenture, Capgemini, MPhasis, HCL, Virtusa, Infosys, TCS, Wipro, NTT etc)

Mandatory (Note): Not looking for implementation engineer but someone who handles the implementation projects

Mandatory (Note): Hike range is 15-35%, Please check with candidate if they are ok

Mandatory (Education): Engineering graduate

We are looking for a Machine Learning Engineer to design, build, and operate production-grade ML systems powering scalable, data-driven applications.

You will be responsible for developing end-to-end machine learning pipelines, ensuring seamless consistency between development and production environments while building reliable and scalable ML infrastructure.

This role focuses on production ML engineering, not experimentation-only data science. You will work closely with backend, data, and product teams to deploy and operate predictive systems at scale.

Requirements

• Strong coding skills in Python, with the ability to build reliable, production-quality systems.
• Experience developing end-to-end machine learning pipelines, ensuring consistency between development, training, and production environments.
• Ability to design and implement scalable ML architectures tailored to site traffic, system scale, and predictive feature complexity.
• Familiarity with model and data versioning, resource allocation, system scaling, and structured logging practices.
• Experience building systems that monitor, detect, and respond to failures across infrastructure resources, data pipelines, and model predictions.
• Hands-on expertise with MLOps tools and workflows for scalable, production-level model deployment and lifecycle management.
• Strong problem-solving abilities and comfort working in a fast-paced, high-ownership environment.

Requirements:

• Bachelor's degree or equivalent in Computer Science.
• 2+ years' experience in frontend development.
• Proficient understanding of HTML5 CSS3 and JavaScript.
• Deep knowledge of cross-browser compatibility issues and ways to work around them.
• Familiarity with one or more frameworks, such as Angular, React, or Knockout.
• Experience with TypeScript, ES6/ES2015 a plus.
• Familiarity with Node.js, npm, and build systems such as webpack, Grunt, or gulp a plus.
• Familiarity using Scrum/Agile development methodologies.

• Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
  • programmatically ingesting data from several static and real-time sources (incl. web scraping)
  • rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
  • performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment

• Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
• Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
• Build data tools to facilitate fast data cleaning and statistical analysis
• Ensure data architecture is secure and compliant
• Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
• Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).

•  Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
• Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
• Expert in shell scripting and writing schedulers
• Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
• Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
• Strong knowledge of data security best practices
• 5+ years experience in a data engineering role
• Science / Engineering graduate from a Tier-1 university in the country
• And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep

Job description

Tech Stack: C#, .NET Core, XUnit, Entity Framework Core, MS SQL Server, PostgreSQL, Git, JIRA, Confluence

Senior (Lead) .NET Developer Responsibilities: -

Interface with product owners and software architects to review and finalize requirements

- Participate in the full SDLC including analysis, design, development, testing, deployment, and support of new features and applications

- Actively lead and participate in agile ceremonies (Standups, Refinements, Retrospectives, Planning, and Requirement’s discussions)

- Communicate effectively, clearly, and thoroughly with the Scrum Team and Stakeholders - Provide innovative solutions to complex problems

- Design, develop and modify software applications/systems according to specifications

- Develop technical documentation including services, object, and data model

- Create high quality code and perform code reviews

- Create unit and integration tests to ensure the code quality and functionality

- Proactively learn and share knowledge of technology and compare advantages and disadvantages of alternative solutions/technologies

- Identify areas needing process improvements and see them through to resolution

- Support and coach other Developers, provide technical guidance

- Help onboard new team members

Job Type: Full-time

What you need to have: