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Ai Data Engineer Job Opening In New Delhi – Now Hiring Tata Consultancy Services


Job description

Job Title: AI Data Engineer

Exp- 4 to 8 years

Location- PAN India


Job Description

Key Responsibilities:


- Build and maintain data infrastructure: Design and construct scalable, reliable data pipelines, storage, and processing systems in the cloud.


- Ensure data quality: Clean, transform, and enrich raw data to create business truth that AI models can use for accurate insights.


- Enable AI/ML: Make data readily available and optimized for consumption by AI and machine learning models.


- Manage cloud services: Work with cloud-specific services for storage, compute, and networking to build an efficient and scalable AI data environment.


- Implement security and governance: Apply security controls to protect data and ensure compliance within the data platforms.


- Monitor and optimize: Continuously monitor data workloads and optimize for performance and cost-effectiveness.

________________________________________

Essential skills and tools


- Cloud Platforms: Deep knowledge of data services at least one major cloud provider (e.G., AWS, Google Cloud).


- Programming Languages: Strong proficiency in Python, Spark and SQL.


- Data Warehousing & Storage: Experience with technologies like Azure Synapse Snowflake, GCP BigQuery, Databricks, AWS Redshift and Data Lake.


- Data Pipelines: Familiarity with tools like Azure Data factory, AWS Glue, Apache Airflow, Kafka and dbt for orchestrating data workflows.


- AI-specific tools: Knowledge of vector databases


- Infrastructure as Code (IaC): Skills in tools like Bicep, Terraform or CloudFormation to automate infrastructure deployment.


- CI/CD: Understanding of continuous integration and continuous deployment pipelines.

________________________________________

Experience with any of the following Cloud Native Data Services:


- Azure: Azure Data Factory, MS Fabric, Azure Databricks, Azure Synapse Analytics, Datalake Gen2 and Azure Dedicated SQL Pool (ADW), Cosmos DB


- AWS: AWS Glue, AWS S3, AWS Athena, AWS Kinesis and AWS Redshift, Dynamo DB


- Google Cloud Platform (GCP): GCP Dataproc, GCP DataFlow, GCP BigQuery, GCP Cloud Storage, Cloud SQL and Pub Sub, Google BigTable, Google Spanner.


Qualifications:


- Bachelor’s or master’s degree in engineering or technology


- Proven experience in building and deploying ETL/ELT solutions in production.


- Strong understanding of Data models and Data pipelines and cloud-native Big data architectures.


- Excellent problem-solving, communication, and collaboration skills.

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Ai Data Potential: Insight & Career Growth Guide


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