Kyndryl Data Engineer Recruitment 2026
Freshers Jobs in Bangalore
| Company | Kyndryl |
|---|---|
| Category | IT |
| Job Type | Full Time |
| Location | Bangalore |
| Experience | 5+ Years |
| Batch Eligible | Any Batch |
| Course | B.E / B.Tech / MCA / M.Tech |
Kyndryl is a global technology services company that designs, builds, manages, and modernizes mission-critical technology systems for businesses worldwide. The company helps organizations transform their IT infrastructure, adopt cloud technologies, and develop innovative digital solutions. Kyndryl offers opportunities to work on enterprise technology projects, collaborate with experienced professionals, and develop in-demand technical skills through continuous learning and professional development.
Kyndryl is hiring an experienced Data Engineer for its Bangalore, Karnataka, office. This full-time opportunity is suitable for IT professionals with 5+ years of experience in data engineering, ETL/ELT processes, cloud data platforms, and data pipeline development.
The selected candidate will contribute to building scalable data infrastructure and modern cloud-native data solutions using Google Cloud Platform (GCP), BigQuery, dbt, Terraform, and CI/CD practices.
The role also involves developing data pipelines for AI applications, implementing Retrieval-Augmented Generation (RAG) architectures, managing vector databases, and building reliable data systems that support AI-powered enterprise solutions.
Candidates should have strong SQL and data engineering skills, experience with relational and NoSQL databases, and knowledge of data modeling, cloud modernization, and DevOps practices.
- Design, develop, and optimize scalable data pipelines and ETL/ELT frameworks.
- Build cloud-native data solutions using Google Cloud Platform and BigQuery.
- Develop data transformation workflows using dbt and modern data engineering tools.
- Implement Infrastructure as Code using Terraform.
- Build and maintain CI/CD pipelines for reliable data deployments.
- Design data pipelines for Retrieval-Augmented Generation (RAG) and AI-powered applications.
- Work with vector databases such as Pinecone, Milvus, and Weaviate.
- Develop semantic layers and knowledge graphs to improve data accessibility and contextual understanding.
- Implement data quality checks and identify personally identifiable information (PII) before data reaches AI models.
- Work with relational and NoSQL databases, including PostgreSQL, DB2, and MongoDB.
- Troubleshoot data pipeline issues and improve performance, reliability, and data quality.
- Collaborate with technical teams, architects, and business stakeholders to deliver effective data solutions.
- Minimum 5+ years of overall IT experience.
- Experience in data engineering, data mining, data storage, and ETL processes.
- Hands-on experience developing and maintaining data pipelines.
- Familiarity with cloud data platforms and tools such as Google Cloud Dataproc, AWS Glue, Databricks, or Azure Synapse.
- Experience with relational and NoSQL databases.
- Strong analytical, problem-solving, and critical-thinking skills.
- Ability to manage multiple projects and collaborate with technical and non-technical teams.
- A degree in Computer Science, Software Engineering, Information Technology, or a related scientific discipline is preferred.
Candidates with experience in cloud modernization, data modeling, and enterprise data architecture will have an advantage.
Core Skills: Data Engineering, SQL, ETL, ELT, Data Pipelines, Data Modeling, Data Warehousing, Data Transformation.
Cloud Technologies: Google Cloud Platform (GCP), BigQuery, Google Cloud Dataproc, AWS Glue, Azure Synapse.
Data Engineering Tools: dbt, Apache Spark, Apache Beam, Hive, Terraform.
Databases: PostgreSQL, IBM Db2, MongoDB, Pinecone, Milvus, Weaviate.
DevOps and Development: CI/CD, DevOps, GitHub, Infrastructure as Code, Cloud Run.
AI and Modern Data Architecture: Retrieval-Augmented Generation (RAG), Vector Embeddings, Vector Databases, Knowledge Graphs, Semantic Layers, AI Data Pipelines.
Data Formats and Architecture: Apache Iceberg, Apache Hudi, Avro, Parquet, Data Mesh.
- Online Application: Submit your application through the official Kyndryl careers portal.
- Resume Screening: The recruitment team reviews relevant experience, technical skills, and qualifications.
- Technical Interview: Candidates may be assessed on SQL, ETL/ELT, data pipelines, cloud platforms, and data engineering concepts.
- Technical or Managerial Discussion: Additional discussions may assess project experience, problem-solving, and collaboration skills.
- Final Selection: Successful candidates receive further communication from the recruitment team regarding the next steps.
Note: The actual selection process may vary depending on the employer's recruitment requirements.
Eligibles can apply for this drive online by clicking the link below. All upcoming interview details, exam schedules, and shortlisting updates will be sent directly to your registered email address.
👉 Click Here to Apply: Kyndryl Official website
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