Jobs at DataZymes Analytics Pvt. Ltd.

Build and maintain scalable AWS data pipelines, warehouses, schemas, and ingestion systems for large structured and unstructured datasets. Develop ETL/ELT workflows using AWS services including Glue, Lambda, S3, Redshift, and CodePipeline. Create dimensional models, analytics tools, and data marts while ensuring data quality, privacy, compliance, and performance. Collaborate with cross-functional stakeholders to resolve data issues, improve infrastructure, and deliver actionable business insights.

Maintain and advance DataZymes’ Databricks capabilities by evaluating new platform features, optimizing costs, shaping architecture standards, and converting proofs of concept into reusable patterns. Provide technical guidance, participate in architecture reviews, track the Databricks roadmap, support partner discussions, and influence certification and enablement priorities. The role requires broad expertise across data engineering, deployment, governance, GenAI, multi-cloud environments, and Databricks platform architecture.

Plan and execute B2B marketing campaigns across email, LinkedIn, digital channels, and events. Manage ABM outreach, social content, CRM data, prospect lists, webinars, and campaign follow-up. Coordinate blogs, case studies, thought leadership, and visual assets. Track marketing KPIs, pipeline contribution, engagement, and social performance, providing actionable reports to leadership and account teams.

Leads pharmaceutical commercial analytics and decision sciences projects, including marketing mix measurement, investment optimization, campaign analytics, segmentation, and performance analytics. Oversees strategic planning, product development, research, client delivery, and cross-functional collaboration. Develops advanced statistical and AI/ML solutions using Python, R, SAS, and SQL while mentoring teams and contributing to thought leadership.

Develop full-stack software solutions for DataZymes, supporting technology-led innovation and healthcare analytics platforms. The role involves contributing to impactful data and analytics initiatives within a high-performance, fast-growing team.

Develop and productionize generative AI applications, including RAG, multi-agent systems, Text2SQL, and fine-tuned models. Own production rollouts, evaluation, and optimization while partnering with product and engineering teams to shape roadmaps. Apply machine learning and data science expertise to business problems, deploy solutions on cloud platforms, and communicate technical concepts to varied audiences. The role also involves collaboration across time zones and may support healthcare and pharmaceutical analytics use cases.

Architects and ships production-grade agentic AI and multi-agent systems for pharmaceutical data, analytics, regulatory, clinical, and medical affairs workflows. Builds RAG pipelines, knowledge graphs, intelligent document processing, observability, evaluation, guardrails, and compliant integrations. Leads AI engineers and ML practitioners, directs architecture, partners with clients on solution delivery, and establishes reusable governance and engineering practices for regulated pharma environments.