Job Location : Hyderabad

Experience : 5 Yr

CTC Budget : 2000000 to 3000000

Posted At : 20-Nov-2025

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• The Senior Data Integration and AI Analytics Specialist is responsible for designing, developing, and maintaining scalable data pipelines and AI analytics workflows to support business intelligence and operational goals.
• This role requires deep expertise in data integration platforms such as Dataiku, cloud data warehousing with Snowflake and AWS, and scripting with Python for automation and data transformation.
• The specialist will collaborate closely with data scientists and business stakeholders to deliver actionable insights, automate complex workflows, and ensure data integrity and efficiency across environments.

Key Responsibilities:

• Develop and maintain ETL workflows integrating data from diverse sources including SQL Server, SAP HANA, Oracle, AWS Redshift, and cloud storage platforms.
• Manage and administer Dataiku environment tasks including license management, credential handling, and environment setup.
• Automate data pipelines, batch processing, and API integrations for efficient and reliable data flow.
• Collaborate with data science teams to prepare data for AI model training and experimentation.
• Implement data validation, monitoring, and reconciliation reporting to reduce manual effort and increase accuracy.
• Develop Python-based tools for auditing, user activity tracking, and process automation within analytics environments.
• Create interactive dashboards to visualize KPIs and provide insights for stakeholders supporting decision-making.
• Document data workflows, requirements, and troubleshooting guides to enhance team knowledge sharing.
• Support cloud infrastructure provisioning and DevOps CI/CD pipelines relevant to data operations.

Required Skills & Qualifications:

• Strong experience with Dataiku DSS for data pipeline development, maintenance, and administration.
• Expertise in SQL and Python (including Pandas, PySpark) for data integration, transformation, and scripting.
• Proficiency in cloud data platforms including Snowflake, AWS (S3, Redshift), and experience with associated DevOps tools.
• Good understanding of ETL design patterns, batch scheduling, and workflow orchestration.
• Familiarity with API automation and data validation techniques.
• Experience working collaboratively in cross-functional teams involving data scientists and business users.
• Strong analytical, problem-solving, and documentation skills with a focus on operational efficiency.
• Certifications in Dataiku Core Designer, Dataiku ML Practitioner, AWS Solution Architect, or Microsoft Azure Fundamentals are preferred.

Experience:
• Minimum 5–8 years of experience in data integration, data engineering, or AI/analytics development roles.
• Hands-on experience in automating complex data workflows and building scalable analytics solutions.
• Previous exposure to cloud infrastructure provisioning and basic DevOps tooling is an advantage.