Data Engineer

Deutsche Telekom Digital Labs • Java • Python • Scala • SQL • ETL/ELT • 1 month ago
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Salary
≈ $17k – $49k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Junior · 2+ years exp
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Deutsche Telekom Digital Labs

DTDL (Digital Transformation and Data Analytics Solutions) is an Indian technology firm specializing in digital solutions, data management, and enterprise IT services. The company provides customized software development, cloud integration, and advanced analytics to help businesses optimize their operations and scale efficiently. Based in India, it serves as a digital transformation partner for organizations looking to leverage technology for business growth and modernization.
dtdl.in • HQ: Gurgaon, India • Information Technology • Telecommunications • Mobile Networks • 1001-5000 employees • Est. 2018

Responsibilities:

  • You will be involved in the design of data solutions using Hadoop-based technologies along with Hadoop and AWS.
  • Responsibilities include design and implementation of various Big Data platform
  • components like batch processing, live stream processing, in-memory cache, query layer (SQL), rule engine, and action framework.
  • Designed and implemented a data access layer, which can connect to various data sources and uses advanced caching techniques to provide fast responses to real-time SQL queries using big data technologies.
  • Implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies: Spark, Kafka, any Cloud computing, etc.

Requirements:

  • 2+ years of data engineering experience.
  • Programming Language: Good hands-on knowledge of one of the programming languages: Java/Scala/Python.
  • Data Store: Good understanding of SQL and NoSQL databases. MySQL, Mongo.
  • Data Infrastructure: Familiar with cloud solutions for data infrastructure. AWS preferably.
  • Data handling frameworks: Good hands-on experience with one of the data-handling frameworks - Spark, Apache Beam, Apache Flink, etc.
  • File formats: Familiar with different types of data formats - Apache Parquet, Avro, ORC, etc.
  • Good understanding of how to set up and optimize the data pipeline and overall infrastructure for setting up ETL jobs.
  • Proficient with distributed file systems and computation concepts.
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