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Senior Technologist - Data Engineering and AI Platforms

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Onsite

Senior Technologist - Data Engineering and AI Platforms

Infosys

Senior Technologist - Data Engineering and AI Platforms

Skills

Big DataData EngineeringTableauData ScienceData VisualizationDatabricksData AnalysisMachine LearningAINLP / Natural Language Processing

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

12 August 2026

What they need


Educational Requirements

Bachelor of Engineering

Service Line

Strategic Technology Group

Responsibilities

  • Data Engineering Architecture: Serve as a hands-on technical leader in the design of scalable data pipelines, data stores, and information flows across the enterprise.
  • Design and optimize cloud-based big data platforms, including ingestion, transformation, storage, and consumption layers.
  • Lead the engineering of ETL/ELT frameworks, streaming pipelines, and batch processing solutions.
  • Conduct enterprise-wide assessments of data stores and data flows to identify bottlenecks, friction points, and modernization opportunities.
  • Own data modeling standards to ensure alignment with business objectives, performance, and accessibility.
  • AI Enablement Advanced Analytics: Enable and support AI/ML and GenAI initiatives by building reliable, high-quality, and well-governed data pipelines.
  • Collaborate with Data Science teams to operationalize models, including feature engineering pipelines, inference data flows, and model monitoring data.
  • Support AI-driven use cases such as predictive analytics, recommendations, NLP-based insights, and intelligent automation.
  • Stay current with market trends, embed innovative practices into strategy, and drive the organization forward with an AI-first approach ensuring AI initiatives move beyond proof-of-concept to enterprise-scale solutions.
  • Approach data engineering with an AI mindset and vice versa, reflecting the evolving and inseparable nature of the two disciplines.

Technical and Professional Requirements:

  • Desired Qualifications: Experience in financial services, with understanding of consumer and commercial banking data.
  • Experience supporting or enabling AI/ML and GenAI solutions, including feature pipelines and analytics platforms.
  • Familiarity with data visualization and BI tools (Tableau, Cognos, SAS).
  • Knowledge of responsible AI, data governance, and regulatory considerations in highly regulated environments.
  • Experience modernizing legacy data platforms into cloud-native architectures.
  • Executive speaking skills ability to articulate strategy, challenge the status quo, and present to senior leadership and key stakeholders with confidence.
  • Experience working across or within highly collaborative, non-hierarchical organizational cultures with an emphasis on peer relationships and open communication.

Preferred Skills:

  • Technology->AI-Generative AI->Generative AI - Basic
  • Technology->Data Engineering->Databricks

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