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AI Data Engineer

AI Data Engineer

Tata Consultancy Servicesdombivli, India
7 days ago
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.

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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.
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    Ai Data Engineer • dombivli, India