AWS Data Engineer Position

2 days ago

Kolkata, West Bengal, India beBeeDataEngineering Full time ₹ 15,24,000 - ₹ 20,31,000
Data Engineering Role

We are seeking skilled professionals to design, develop, and manage robust data pipelines that power AI-driven workflows and applications on cloud-native environments.

The role focuses on developing efficient ETL/ELT workflows, ensuring data quality, security, and scalability to support model training, inference, and intelligent decision-making processes. The ideal candidate will have 3-7 years of experience in data engineering, building data pipelines, and cloud-based data solutions with strong programming skills in Python, SQL, and/or Scala/Java, as well as expertise in AWS cloud services including S3, Glue, EMR, Redshift, Athena, Kinesis, Lambda, Step Functions, DynamoDB, and RDS.

The successful candidate will be able to design, develop, and maintain ETL/ELT pipelines to process structured, unstructured, and streaming data in AWS environments, ensuring robust data governance, security, and quality controls throughout the data lifecycle, supporting regulatory compliance.

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:
  • 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).
  • 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 Attributes:
  • 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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