Cloud Native Data Solutions Architect

2 days ago

Kannur, Kerala, India beBeeData Full time ₹ 18,86,769 - ₹ 26,29,846

We are seeking skilled professionals to join our team as Data Engineers, with a focus on designing and building robust data pipelines that power Agentic AI solutions on AWS. This role involves developing efficient ETL/ELT workflows, ensuring data quality, security, and scalability to support AI/ML model training, inference, and intelligent decision-making processes in a cloud-native environment.

Key Responsibilities:
  • Design, develop, and maintain ETL/ELT pipelines to process structured, unstructured, and streaming data in AWS environments.
  • Leverage AWS services such as S3, Glue, EMR, Lambda, Kinesis, Step Functions, Redshift, Athena, DynamoDB, RDS, and Lake Formation for scalable data ingestion, transformation, storage, and querying.
  • Ensure robust data governance, security, and quality controls throughout the data lifecycle, supporting regulatory compliance.
  • Enable both real-time and batch data processing pipelines to power AI-driven workflows and applications.
  • 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, scalability, reliability, and cost efficiency.
  • Implement CI/CD pipelines and data engineering best practices in a cloud-native architecture for automated deployments.
  • Monitor, debug, and resolve issues in data pipelines to ensure high availability, reliability, and minimal latency.
Required Skills & Qualifications:
  • Strong background in software development, particularly in Python, SQL, and/or Scala/Java programming languages.
  • Hands-on experience in Data Engineering, building data pipelines, and cloud-based data solutions, preferably with 3–7 years of industry experience.
  • Excellent knowledge of big data frameworks like Apache Spark, Hadoop, or Flink, and their integration with cloud services.
  • Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, Dagster, or similar.
  • Proficiency in data modeling, data warehousing concepts, and schema design principles.
  • Familiarity with DevOps practices, including Infrastructure as Code (Terraform, CloudFormation), CI/CD automation, Git, and containerization (Docker).
Preferred Attributes:
  • Able to work effectively in regulated industries, particularly in healthcare and Life Sciences, with a focus on compliance and data privacy.
  • Excellent problem-solving skills and strong collaboration abilities, ensuring seamless interaction with cross-functional teams.
  • Passion for designing innovative, scalable, and efficient cloud-native data solutions.

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