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Data Engineer

Exclusive opportunity

Onsite

Data Engineer

TECHNIX TECHNOLOGY

Data Engineer

Skills

Google Cloud PlatformSQL QueriesBig DataPythonJavaMySQLKafkaData AnalysisScalaAWSApache AirflowHadoopAzure

2 years ago

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Important information


Contract type:

Permanent

Location:

Bangladesh

Work mode:

Onsite

Published on:

7 August 2026

What they need


Patna

Opening: 20-Dec-2023

Skills Required: Python, Java/Scala, SQL, Scripting languages (Bash, Shell), Apache Spark, Scala, Airflow, Hadoop, Kafka, AWS/Azure/GCP, SQL and NoSQL databases

Experience Required: Minimum of 2 Years

Educational Qualification: Bachelor's degree in Computer Science, Information, Engineering or another quantitative field

Employment Type: Full Time

Workplace Options: Onsite

Opening Summary

We are looking for an experienced data engineer to join our team. Data Engineers uses various methods to transform raw data into useful data systems. They will create algorithms and conduct statistical analysis. Overall, Data Engineers are strive for efficiency by aligning data systems with business goals.

Requirements

  • Passion for testing strategy, problem-solving, and continuous learning.
  • Willingness to acquire new skills and knowledge.
  • Possess a product/engineering mindset to drive impactful data solutions.
  • Experience working in distributed environments with global teams.
  • Knowledge or experience in architectural best practices for building data lakes.
  • Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
  • Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
  • Experience with RDBMS and OLAP databases like MySQL, Redshift.
  • Solid understanding of batch and streaming data processing techniques
  • High proficiency in Scala/Java and Spark for applied large-scale data processing.

Responsibilities

  • Analyze and organize raw data
  • Build data systems and pipelines
  • Evaluate business needs and objectives
  • Interpret trends and patterns
  • Conduct complex data analysis and report on results
  • Prepare data for prescriptive and predictive modeling
  • Build algorithms and prototypes
  • Combine raw information from different sources
  • Explore ways to enhance data quality and reliability
  • Identify opportunities for data acquisition
  • Develop analytical tools and programs
  • Collaborate with data scientists and architects on several projects

Notes

  • Joining time should not be longer than 15 days.

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