Description

You will design and implement large-scale data processing pipelines and storage architectures.

This role is on-site.

Responsibilities

• Build and maintain data pipelines using batch, micro-batching, and streaming methodologies.
• Implement data modeling techniques such as Dimensional, Data Vault, Kimball, or Inmon.
• Develop and execute PI plans and roadmaps within an Agile environment.
• Apply TDD or BDD practices and manage deployments via CI/CD tools.
• Document technical architectures and data workflows clearly.

Required Skills

• 5+ years of experience in data engineering.
• Proficiency in Python, Scala, or Java.
• Experience with cluster computing frameworks like Spark, Flink, or Storm.
• Hands-on with cloud data lakehouse platforms such as AWS data lake services, Databricks, or Hadoop.
• Proficiency in relational stores (Postgres, Oracle) and NoSQL stores (Cassandra, Dynamo, MongoDB).
• Experience with orchestration tools like Airflow or AWS Step Functions.
• Knowledge of data structures and serialization formats including JSON, Avro, or Protobuf.
• Experience with big-data storage formats like Parquet or Iceberg.
• Proficiency with Git and Jenkins for CI/CD.

Preferred Skills

• Experience using AWS Bedrock APIs and Generative AI concepts like RAG, Vector embeddings, or Agentic AI.
• Experience with Infrastructure as Code using Terraform or AWS CloudFormation.

Key Skills

Education

Any Gradute