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2 Days ago

Data Engineer

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Bangalore, Karnataka, India
Information Technology
Full-Time
Bristlecone

Overview

Job Summary

JOB DESCRIPTION

We are seeking a talented and experienced Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and systems to support analytics and data-driven decision-making. This role requires expertise in data processing, data modeling, and big data technologies.

Responsibilities

Key Responsibilities:

  • Design and develop datapipelines to collect, transform, and load data into datalakes and datawarehouses .
  • Optimize ETLworkflows to ensure data accuracy, reliability, and scalability.
  • Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements.
  • Implement and manage cloud − baseddataplatforms (e.g., AWS , Azure , or GoogleCloudPlatform ).
  • Develop datamodels to support analytics and reporting.
  • Monitor and troubleshoot data systems to ensure high performance and minimal downtime.
  • Ensure data quality and security through governance best practices.
  • Document workflows, processes, and architecture to facilitate collaboration and scalability.
  • Stay updated with emerging data engineering technologies and trends.

Qualifications

Required Skills and Qualifications:

  • Strong proficiency in SQL and Python for data processing and transformation.
  • Hands-on experience with bigdatatechnologies like ApacheSpark , Hadoop , or Kafka .
  • Knowledge of datawarehousingconcepts and tools such as Snowflake , BigQuery , or Redshift .
  • Experience with workfloworchestrationtools like ApacheAirflow or Prefect .
  • Familiarity with cloudplatforms (AWS, Azure, GCP) and their data services.
  • Understanding of datagovernance , security , and compliance best practices.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration abilities.

Preferred Qualifications

  • Certification in cloudplatforms (AWS, Azure, or GCP).
  • Experience with NoSQLdatabases like MongoDB , Cassandra , or DynamoDB .
  • Familiarity with DevOpspractices and tools like Docker , Kubernetes , and Terraform .
  • Exposure to machinelearningpipelines and tools like MLflow or Kubeflow .
  • Knowledge of datavisualizationtools like PowerBI , Tableau , or Looker .
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