Cloud Data Architect

1 day ago

Dindigul, Tamil Nadu, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

We are seeking an experienced Data Engineer to join our team and help design, build, and manage robust data pipelines that power AI-driven solutions on AWS. The role focuses on developing efficient ETL/ELT workflows, ensuring data quality, security, and scalability in a cloud-native environment.

About the Role:

This is an exciting opportunity for a skilled Data Engineer to collaborate closely with AI/ML teams to prepare clean, high-quality datasets optimized for model training, inference, and fine-tuning. You will be responsible for designing, developing, and maintaining scalable data ingestion, transformation, storage, and querying pipelines using AWS services such as S3, Glue, EMR, Lambda, Kinesis, Step Functions, Redshift, Athena, DynamoDB, RDS, and Lake Formation.

Key Responsibilities:
  • Design, develop, and maintain scalable data ingestion, transformation, storage, and querying pipelines using AWS services.
  • Ensure robust data governance, security, and quality controls throughout the data lifecycle, supporting regulatory compliance and minimizing latency.
  • Collaborate closely with AI/ML teams to prepare clean, high-quality datasets optimized for model training, inference, and fine-tuning.
  • Optimize data infrastructure to achieve high performance, reliability, and cost efficiency, implementing CI/CD pipelines and data engineering best practices.
Requirements:
  • 3–7 years of hands-on experience in Data Engineering, building data pipelines, and cloud-based data solutions.
  • Strong programming skills in Python, SQL, and/or Scala/Java.
  • Expertise in AWS cloud services, including S3, Glue, EMR, Redshift, Athena, Kinesis, Lambda, Step Functions, DynamoDB, and RDS.
  • Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, Dagster, or similar.
  • Proficiency in big data frameworks like Apache Spark, Hadoop, or Flink.
  • Solid understanding of data modeling, data warehousing concepts, and schema design principles.
  • In-depth knowledge of data governance, lineage, security policies (IAM roles, encryption, Lake Formation).

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