Chief Data Architecture Specialist

2 weeks ago

Morādābād, Uttar Pradesh, India beBeeDataEngineer Full time ₹ 1,00,00,000 - ₹ 2,50,00,000

Job Opportunity:

We are seeking a skilled Cloud Data Architect to design, build, and manage robust data pipelines that power AI solutions on AWS.

The role focuses on 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.
  • Maintain thorough documentation of data pipelines, architecture, and processes to facilitate reproducibility and knowledge transfer.
Requirements:
  • 3–7 years of hands-on experience in Cloud 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).
  • Hands-on experience in managing real-time streaming data using Kafka, Kinesis, or equivalent tools.
  • Familiarity with DevOps practices, including Infrastructure as Code (Terraform, CloudFormation), CI/CD automation, Git, and containerization (Docker).
Preferred Qualifications:
  • Experience working in regulated industries (healthcare, Life Sciences) with a focus on compliance and data privacy.
  • Strong problem-solving skills and ability to work in a collaborative, cross-functional team environment.
  • Passion for designing scalable and efficient cloud-native data solutions.
  • Excellent documentation skills, ensuring clear communication of technical solutions and architecture.

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