Master Data Management (MDM): Design and implement MDM strategies to ensure data consistency, quality, and accuracy across multiple systems. ETL Development: Develop, maintain, and optimize ETL pipelines to extract, transform, and load data from various sources into data warehouses or data lakes. AWS Services: Utilize AWS cloud technologies (such as Redshift, S3, Lambda, and EC2) to support scalable and cost-effective data storage and processing solutions. Data Analysis & Reporting: Develop interactive dashboards and reports in Tableau to visualize key business metrics and provide actionable insights to stakeholders. Python & SQL Development: Write efficient Python scripts and SQL queries to process, manipulate, and analyze large datasets. Data Integration: Integrate data from various internal and external systems, ensuring seamless data flows and supporting business needs. Data Quality Assurance: Ensure high data quality standards are met by performing regular data validation, cleansing, and enrichment processes. Collaboration: Work closely with cross-functional teams (data scientists, business analysts, IT) to understand business requirements and translate them into effective data solutions. Performance Optimization: Continuously monitor and optimize data processing and reporting systems to improve efficiency and reduce processing time. Documentation: Maintain comprehensive documentation for ETL processes, data pipelines, and dashboard designs.
Job Summary: We are seeking a highly skilled Lead Data Engineer/Associate Architect to lead the design, implementation, and optimization of scalable data architectures. The ideal candidate will have a deep understanding of data modeling, ETL processes, cloud data solutions, and big data technologies. You will work closely with cross-functional teams to build robust, high-performance data pipelines and infrastructure to enable data-driven decision-making. Experience: 7 - 12 years Work Location: Hyderabad (Hybrid) / Remote Mandatory skills: AWS, Python, SQL, Airflow, DBT Must have done 1 or 2 projects in Clinical Domain/Clinical Industry. Responsibilities: Design and develop scalable and resilient data architectures that support business needs, analytics, and AI/ML workloads. Data Pipeline Development: Design and implement robust ETL/ELT processes to ensure efficient data ingestion, transformation, and storage. Big Data & Cloud Solutions: Architect data solutions using cloud platforms like AWS, Azure, or GCP, leveraging services such as Snowflake, Redshift, BigQuery, and Databricks. Database Optimization: Ensure performance tuning, indexing strategies, and query optimization for relational and NoSQL databases. Data Governance & Security: Implement best practices for data quality, metadata management, compliance (GDPR, CCPA), and security. Collaboration & Leadership: Work closely with data engineers, analysts, and business stakeholders to translate business requirements into scalable solutions. Technology Evaluation: Stay updated with emerging trends, assess new tools and frameworks, and drive innovation in data engineering. Required Skills: Education: Bachelor's or master's degree in computer science, Data Engineering, or a related field. Experience: 7 - 12+ years of experience in data engineering Cloud Platforms: Strong expertise in AWS data services. Databases: Hands-on experience with SQL, NoSQL, and columnar databases such as PostgreSQL, MongoDB, Cassandra, and Snowflake. Programming: Proficiency in Python, Scala, or Java for data processing and automation. ETL Tools: Experience with tools like Apache Airflow, Talend, DBT, or Informatica. Machine Learning & AI Integration (Preferred): Understanding of how to architect data solutions for AI/ML applications
We are seeking a highly skilled and motivated Machine Learning Specialist with a strong background in data science and a deep understanding of clinical supply chain operations . This role will be instrumental in developing predictive models, optimizing logistics, and driving data-driven decision-making across our clinical trial supply chain. Key Responsibilities: Design, develop, and deploy machine learning models to forecast clinical supply needs, optimize inventory, and reduce waste. Collaborate with clinical operations, supply chain, and IT teams to identify data sources and integrate ML solutions into existing workflows. Analyze large datasets from clinical trials, logistics systems, and external sources to uncover trends and actionable insights. Develop tools and dashboards to support real-time decision-making and scenario planning. Ensure model performance, scalability, and compliance with regulatory standards (e.g., GxP, 21 CFR Part 11). Stay current with advancements in ML/AI and apply best practices to clinical supply chain challenges. Qualifications: Masters or PhD in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in machine learning, data science, or AI, preferably in a healthcare or life sciences setting. Hands-on experience with clinical supply chain processes, including demand forecasting, IRT systems, and logistics planning. Proficiency in Python, R, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Strong understanding of statistical modeling, time series forecasting, and optimization techniques. Excellent communication skills and ability to work cross-functionally in a fast-paced environment. Preferred: Experience with clinical trial data (e.g., EDC, CTMS, IRT). Familiarity with regulatory requirements in clinical research. Knowledge of cloud platforms (AWS, Azure, GCP) and MLOps practices.
We are seeking a Tableau Sr. Developer with 5 years of experience in designing, developing, and deploying business intelligence solutions. The ideal candidate will have a deep understanding of data visualization principles, experience in data analysis, and a proven track record of delivering impactful dashboards and reports. You will work closely with stakeholders across the organization to turn complex data sets into easy-to-understand visual stories. Key Responsibilities: Dashboard Development: Design, develop, and maintain interactive Tableau dashboards, reports, and visualizations that meet business needs and provide actionable insights. Ensure the scalability and performance of Tableau solutions by optimizing queries and visualizations. Data Analysis: Analyze and interpret complex data sets from multiple sources to identify trends, patterns, and insights. Collaborate with data analysts and data engineers to define data requirements, create data models, and prepare datasets for visualization. Stakeholder Collaboration: Work closely with business stakeholders to gather requirements, understand business objectives, and translate them into effective visual solutions. Present findings and recommendations to non-technical audiences, ensuring that insights are accessible and actionable. Create backlogs , stories and manage sprints in Jira. Data Integration: Connect Tableau to various data sources, including databases, cloud services, and APIs, ensuring data accuracy and consistency. Develop and maintain data extraction, transformation, and loading (ETL) processes as needed. Best Practices & Training: Stay up-to-date with Tableaus latest features and industry trends to continuously improve the organizations BI capabilities. Provide training and support to end-users to maximize the adoption and usage of Tableau across the organization. Qualifications: Education: Bachelors degree in Computer Science, Information Systems, Data Science, or a related field. Experience: 5+ years of hands-on experience as a Tableau Developer. Proven experience in creating complex dashboards and visualizations using Tableau Desktop and Tableau Server. Strong understanding of SQL and experience in writing complex queries. Experience with data warehousing concepts, ETL processes, and data modeling. Skills: Proficiency in Tableau Desktop, Tableau Server, and Tableau Prep. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. Familiarity with other BI tools (e.g., Power BI, QlikView) is a plus. Excellent communication skills, with the ability to convey technical information to non-technical stakeholders. Experience with Agile project management tools like Jira, gathering requirements and creating stories. Preferred Qualifications: Experience with programming languages like Python or R for advanced data manipulation. Knowledge of cloud platforms (e.g., AWS, Azure) and experience with cloud-based data sources. Tableau certification (e.g., Tableau Desktop Specialist, Tableau Server Certified Associate) is a plus.
Designation - Agentic AI Developer Work Location - Hyderabad (Hybrid) Experience - 0 to 2 years Key Responsibilities Agentic AI Development: Build, customize, and deploy AI agents using frameworks like LangChain, AutoGen, CrewAI, and Haystack. Enable agent reasoning, planning, and tool-use for complex tasks. RAG Pipeline Design: Implement and optimize RAG pipelines for enterprise-scale knowledge retrieval. Work with vector databases (Pinecone, FAISS, Weaviate, Milvus) to manage embeddings and context injection. Fine-tune retrieval strategies, chunking logic, and metadata tagging for high-quality responses. Prompt Engineering & LLM Integration: Develop structured prompts, context-aware query chains, and workflows for LLMs (OpenAI, Anthropic, Llama, Mistral, etc.). Integrate RAG-enabled LLMs into APIs, chatbots, and enterprise applications. Automation & Platform Development: Create orchestration pipelines for AI agents and RAG workflows. Contribute to building internal AI platforms, dashboards, and monitoring systems. Experimentation & Research: Stay current with new developments in RAG, multi-agent systems, and reasoning models. Rapidly prototype AI solutions to demonstrate value to business teams. Required Skills Programming: Strong in Python; familiarity with JavaScript/TypeScript or Go is a plus. LLM Frameworks: Experience or coursework in LangChain, LlamaIndex, Haystack, or AutoGen. RAG Expertise: Understanding of RAG concepts, document indexing, embeddings, retrieval strategies, and vector DBs. Databases: PostgreSQL/MySQL for structured data; Pinecone, Weaviate, Milvus, FAISS for vectors. APIs & Cloud: Knowledge of REST/GraphQL APIs and cloud services (AWS/GCP/Azure). Version Control: Git, GitHub/GitLab, and CI/CD pipelines. Preferred Skills (Good-to-Have) Familiarity with LangGraph and other agent orchestration libraries. Exposure to multi-agent collaboration patterns and reasoning models (OpenAI o1, DeepSeek-R1). Knowledge of document preprocessing , semantic search , and hybrid retrieval . Understanding of MLOps for deploying and monitoring AI pipelines. Experience with Docker, Kubernetes, and distributed systems. Qualifications Bachelors degree in Computer Science, Engineering, AI/ML, or related field. 03 years of relevant experience (internships, hackathons, or open-source contributions preferred). Strong analytical skills, eagerness to experiment, and enthusiasm to learn cutting-edge AI tools.