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Experience: 5+ yrs
Location: Hyderabad, Telangana, India, Bengaluru, Karnataka, India, Gurgaon, Haryana, India
As a Specialist Data Analytics Alteryx, you will design, develop, and optimize end‑to‑end analytical workflows to transform raw data into actionable insights, driving business decisions across multiple domains. Leveraging your deep expertise in Alteryx, you will build reusable data pipelines, perform advanced statistical modeling, and integrate external data via APIs and web services to create comprehensive data ecosystems. You will collaborate closely with data science, engineering, and business stakeholders to define problem statements, select appropriate modeling techniques, and present findings through interactive dashboards and automated reports. Your role will also involve staying abreast of emerging technologies such as Generative AI, and evaluating how these can be embedded into existing workflows to enhance predictive capabilities and streamline data processing.
Requirements
• Design, develop, and maintain scalable Alteryx workflows for data extraction, transformation, and loading (ETL).
• Build and validate statistical and machine learning models in Python and integrate them within Alteryx environments.
• Create and manage API connections to ingest data from internal and external sources, ensuring data integrity and security.
• Implement Gen AI techniques to generate synthetic data and augment training datasets, improving model robustness.
• Automate repetitive data tasks and reporting processes using Alteryx Scheduler and custom scripts.
• Collaborate with data engineers to establish data quality standards, perform profiling, and create documentation.
• Conduct performance tuning of data models and workflows to optimize run times and resource utilization.
• Design visual analytics dashboards using Alteryx, Tableau or Power BI for stakeholder consumption.
• Mentor junior analysts and provide technical guidance on best practices in data modeling and analytics.
• Stay updated on industry trends and emerging tools, proposing continuous improvement initiatives for analytics capabilities.
• 5+ years of hands‑on experience in data analytics, with a strong focus on Alteryx platform.
• Proficiency in Python, including libraries such as pandas, scikit‑learn, and PySpark for advanced modeling.
• Demonstrated expertise in designing robust data models and building end‑to‑end data pipelines.
• Experience integrating APIs (REST, SOAP) and handling various data formats (JSON, XML, CSV).
• Familiarity with Generative AI concepts and practical application in data augmentation or predictive modeling.
• Strong problem‑solving skills with a track record of delivering data solutions that drive business value.
• Excellent communication abilities, able to translate complex technical findings into clear, actionable insights for non‑technical stakeholders.
• Proven ability to work collaboratively in cross‑functional teams across multiple geographies (Hyderabad, Bengaluru, Gurgaon).
• Strong documentation practices, ensuring reproducibility and maintainability of analytical solutions.
• Passion for continuous learning and staying current with evolving analytics technologies and industry best practices.
From live job posts on CoreHRx, updated 2 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.
The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹10L – ₹24L a year (typical for IT Jobs in India, 906 posts).
The post asks for 5 Yrs experience.
It is a full time job.
You apply on Weekday AI's website. CoreHRx takes you there after you sign in.
Interview preparation · 60 questions
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
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