Systems Integration Specialist Advisor

NTT DATA BUSINESS SOLUTIONS; Bengaluru; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS in Bengaluru, India seeks a Senior Data Analyst to turn complex data into actionable insights, designing and implementing data products on Microsoft Azure to solve business problems. You will architect data pipelines, optimize warehouses, and collaborate with stakeholders to translate requirements into scalable analytics, with a focus on data quality and governance.

Strong SQL, Python, Azure, and experience with Spark, Databricks, Kafka, and containerization are

Job description

We are currently seeking a Systems Integration Specialist Advisor to join our team in Bengaluru, Karnataka, India.

Job Description

Seeking a Senior Data Analyst who thrives on turning complex data into actionable insights. In this role, youll lead the design and implementation of data products on the Microsoft Azure platform, leveraging cutting-edge cloud-native solutions to solve challenging business problems and deliver meaningful outcomes.

What Youll Do

• Partner with stakeholders to gather requirements and translate them into impactful data solutions.
• Design and optimize data architectures, pipelines, and warehouses to enable scalable analytics.
• Perform deep-dive analysis on large, structured datasets to uncover trends and drive decisions.
• Document data flows and ensure clarity from source to target.
• Collaborate with cross-functional teams to deliver insights that answer critical business questions.
• Communicate findings through clear storytelling, both written and verbal, to technical and non-technical audiences.
• Champion data quality, governance, and security across all solutions.

What you bring

• Experience across the data pipeline: acquisition, preparation, and architecture.
• Strong proficiency in SQL and Python for data analysis and automation.
• Hands-on experience with Azure services, including deployment automation (PowerShell/Azure CLI).
• Familiarity with modern data tools: Spark, Databricks, Hadoop, Kafka, and data warehousing.
• Exposure to real-time data streaming and containerization (Docker, Kubernetes).
• Understanding of data engineering principles supporting AI/ML initiatives.
• Experience with Agile practices and collaborative team environments.
• Excellent communication skills and ability to translate technical insights into business value.