3+ Domain management Jobs in India

Role Overview

The Data / Business Analyst plays a key role in Customer’s Data Hub initiative, supporting the delivery of standardized, trusted, and compliant regulatory data across the organization. This role act as the bridge between business requirements, data governance, and technical implementation ensuring that data pipelines, models, and mappings are accurate, validated, and ready for business use.

Key Responsibilities

Collaborate with source system owners and regulatory stakeholders to gather and refine data pipeline requirements.

Translate data pipeline requirements into epics and stories ready for refinement in Jira.

Lead backlog refinement sessions with data architects, domain leads, and scientists to prioritize data ingestion and transformation activities.

Define story structure to comprise the requirements of the work to be done and the definition of done and the different types of tasks relevant for the domain to accomplish with their associated roles, documented in a Confluence page.

Endorse the role of agile scrum master for the RDH team: coach team members in self-management, organize high-value increments in sprints meeting the definition of done

Identify and document potential data issues including quality, normalization, duplication, completeness, or governance gaps and share findings with the Data Domain and platform Lead.

Work closely with Data Architects to define and document the data transformation pipeline architecture.

Support the Data Architect in defining and maintaining the data models used across regulatory use cases by reviewing proposed changes and evaluate their relevance towards new requirements.

Support the review phase led by the Data Domain Lead, verifying that the regulatory and business context is preserved across transformed datasets.

Validate that all data mappings and transformations meet regulatory compliance, data quality, and analytical readiness standards.

Collaborate with Data Scientists to define mapping logic for regulatory entities such as substances, studies, and documents.

Review the design of quality control pipelines, ensuring mapping accuracy and alignment with analytical expectations.

Key Deliverables

Comprehensive and well-documented data pipeline and transformation specifications

Defined and validated data models and business-aligned mapping definitions

Clear and traceable backlog refinement inputs and prioritization documentation

Continuous collaboration and feedback loop with the Data Domain Lead, Platform Lead and Data Science teams

Skills and Qualifications

Bachelor’s degree in data analytics, computer science

5+ years of experience in data or business analysis e.g., Life Sciences, Agrochemical, or Pharma domain

Demonstrated expertise in data transformation pipelines, and data quality frameworks

Familiarity with metadata management and data governance principles

Strong analytical skills, with the ability to translate business requirements into technical deliverables

Excellent communication and documentation skills, with experience collaborating across disciplines e.g. Data Scientists, Architects, Domain Leads, Platform Leads

A collaborative and proactive approach, comfortable working in iterative, agile environments

High attention to detail with strong problem-solving capabilities

Self-motivated and adaptable, able to navigate ambiguity and evolving project priorities in a complex data environment

Are you a motivated individual eager to launch your career in generative AI and learn advanced technologies? Are you a hands-on learner with an interest in large language models and emerging AI technologies? Do you possess the ability to collaborate effectively within a team environment to implement and learn technical solutions?

At Aivar, we're looking for entry-level architects and engineers to learn generative AI techniques and contribute to building innovative solutions under the guidance of experienced professionals.

As an Generative AI/ML Engineer, you'll learn from technology and business teams while developing solutions. You will gain hands-on experience in a fast-paced environment that contributes to innovative AI projects.

Key job responsibilities:

● Learn to implement large language model solutions using Amazon Web Services (AWS)

● Learn Generative AI frameworks (LangChain, LangSmith, HuggingFace)

● Support prompt engineering implementation

● Assist in fine-tuning pipelines for specific use cases

● Learn to build basic generative AI solutions for text and images

● Help implement RAG architectures

● Support MLOps/LLMOps practices

● Document implementations and learnings

● Assist in testing generative AI solutions

Job Description:

• Create email marketing campaigns to promote products or services.
• Ensure marketing message is conveyed clearly and delivered properly to prospects.
• To fix bad domain reputation, IP reputation
• Knowledge of Spam rate, resolving any impromptu issue related to the backend of email marketing
• Follow up on interested respondents.
• Purge non-deliverable email addresses and opt-outs.
• Track and analyze direct and interactive marketing campaigns.
• Use statistical analysis and reports to create campaigns.
• Provide recommendations for new and existing campaigns including triggers, and automation
• Build creative, messaging, and content for campaigns using email and automated marketing

Required Candidate Profile:

1. Minimum 1 year of experience in Email marketing, bulk emailing & email campaigns.
2. Should have experience in generating leads through email marketing, Data mining, and database development using different tools.
3. Should have knowledge of lead data extraction from search engines and other lead portals.