Senior Data Science Specialist

HCLTech • IT Consulting & Digital Transformation • IT Outsourcing & Dedicated Teams • 1 day ago
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Salary
≈ $57k – $149k per year (Estimated)
Location
In office (Malmö)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 13, 2026.

Overview
Company
Impact
Profile match

HCLTech

HCLTech is a major Indian multinational information technology (IT) services and consulting company headquartered in Noida, Uttar Pradesh. Spun off from the original HCL Group in 1991, it ranks as one of India's largest technology companies alongside firms like TCS, Infosys, and Wipro.
hcltech.com • HQ: Noida, India • Systems Integrators • IT Consulting & Digital Transformation • IT Outsourcing & Dedicated Teams • 5000+ employees • Est. 1976
Tech stack of HCLTech

Job Summary

We are looking for a Databricks expert with strong experience in platform setup, architecture, and AI/ML capabilities across Azure and/or GCP. The ideal candidate should bring hands-on expertise in building Databricks-based AI solutions, not just traditional data pipelines.

Key Responsibilities

  • Design and implement Databricks architecture on Azure and/or GCP (workspace, clusters, networking, security).
  • Lead platform setup, governance, and optimization (Unity Catalog, cost control, access management).
  • Build and deploy AI/ML solutions using Databricks (MLflow, Feature Store, Model Serving).
  • Develop GenAI / LLM solutions (RAG pipelines, embeddings, vector search).
  • Integrate LLMs (Azure OpenAI / Vertex AI / other APIs) within Databricks.
  • Deliver scalable Lakehouse architecture solutions.
  • Collaborate with engineering and business teams for end-to-end AI use cases.
  • Ensure performance tuning, reliability, and security of workloads

Skill Requirements

  • Design and implement Databricks architecture on Azure and/or GCP (workspace, clusters, networking, security).
  • Lead platform setup, governance, and optimization (Unity Catalog, cost control, access management).
  • Build and deploy AI/ML solutions using Databricks (MLflow, Feature Store, Model Serving).
  • Develop GenAI / LLM solutions (RAG pipelines, embeddings, vector search).
  • Integrate LLMs (Azure OpenAI / Vertex AI / other APIs) within Databricks.
  • Deliver scalable Lakehouse architecture solutions.
  • Collaborate with engineering and business teams for end-to-end AI use cases.
  • Ensure performance tuning, reliability, and security of workloads

Other Requirements

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