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Technical Specialist

India

Job Description

Technical Specialist

Hyderabad, Telangana

Job Summary

AI, Machine Learning, Kafka, Big Query

- Design and develop batch and real-time data pipelines for analytics, AI, and machine learning use cases.
- Build Kafka producers, consumers, topics, connectors, and stream-processing workflows with appropriate partitioning, ordering, replay, retry, and dead-letter handling.
- Create and optimize BigQuery datasets, tables, views, materialized views, partitioning, clustering, and SQL workloads for performance and cost efficiency.
- Integrate structured and unstructured data from applications, APIs, databases, files, and event streams.
- Prepare curated, reusable datasets and feature pipelines for model training, validation, deployment, and monitoring.
- Implement data-quality checks, schema validation, lineage, metadata, retention, and access controls.
- Develop reliable orchestration, CI/CD, automated testing, observability, and incident-response practices for data workloads.
- Troubleshoot pipeline failures, data delays, duplication, schema changes, and performance bottlenecks.
- Collaborate with data scientists to operationalize machine learning workflows and ensure reproducible data inputs.
- Document data models, interfaces, operational procedures, and architectural decisions.

Mandatory Technical Skills
- Robust programming skills in Python and advanced SQL.
- Hands-on experience with Apache Kafka or a managed Kafka service in production environments.
- Strong expertise in Google BigQuery, including data modeling, query optimization, partitioning, clustering, and cost management.
- Practical knowledge of ETL/ELT patterns, dimensional modeling, data lakes, data warehouses, and distributed processing.
- Experience building data pipelines for AI and machine learning workloads.
- Knowledge of machine learning lifecycle concepts, feature engineering, model inputs and outputs, and production monitoring.
- Experience with Google Cloud data services and cloud-native security practices.
- Proficiency with workflow orchestration, version control, automated testing, and CI/CD.
- Understanding of data governance, privacy, access management, encryption, and audit requirements.
- Strong diagnostic and performance-tuning skills across streaming and analytical workloads

Key Responsibilities

AI, Machine Learning, Kafka, Big Query

- Design and develop batch and real-time data pipelines for analytics, AI, and machine learning use cases.
- Build Kafka producers, consumers, topics, connectors, and stream-processing workflows with appropriate partitioning, ordering, replay, retry, and dead-letter handling.
- Create and optimize BigQuery datasets,



tables, views, materialized views, partitioning, clustering, and SQL workloads for performance and cost efficiency.
- Integrate structured and unstructured data from applications, APIs, databases, files, and event streams.
- Prepare curated, reusable datasets and feature pipelines for model training, validation, deployment, and monitoring.
- Implement data-quality checks, schema validation, lineage, metadata, retention, and access controls.
- Develop reliable orchestration, CI/CD, automated testing, observability, and incident-response practices for data workloads.
- Troubleshoot pipeline failures, data delays, duplication, schema changes, and performance bottlenecks.
- Collaborate with data scientists to operationalize machine learning workflows and ensure reproducible data inputs.
- Document data models, interfaces, operational procedures, and architectural decisions.

Mandatory Technical Skills
- Strong programming skills in Python and advanced SQL.
- Hands-on experience with Apache Kafka or a managed Kafka service in production environments.
- Strong expertise in Google BigQuery, including data modeling, query optimization, partitioning, clustering, and cost management.
- Practical knowledge of ETL/ELT patterns, dimensional modeling, data lakes, data warehouses, and distributed processing.
- Experience building data pipelines for AI and machine learning workloads.
- Knowledge of machine learning lifecycle concepts, feature engineering, model inputs and outputs, and production monitoring.
- Experience with Google Cloud data services and cloud-native security practices.
- Proficiency with workflow orchestration, version control, automated testing, and CI/CD.
- Understanding of data governance, privacy, access management, encryption, and audit requirements.
- Strong diagnostic and performance-tuning skills across streaming and analytical workloads.

Preferred Skills

Skill Requirements

Other Requirements

Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion.

Copyright © 2026 HCL Technologies Limited

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📌 Technical Specialist (India)
🏢 HCLTech
📍 India