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Data Engineer

Evnek

Role overview

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
  • 2–4 years of hands-on experience in Data Engineering.
  • Experience working with cloud platforms, preferably Microsoft Azure.
  • Strong understanding of data integration, transformation, and pipeline development.

Responsibilities

  • Develop, maintain, and optimize ETL/ELT pipelines for data integration and processing.
  • Build data processing applications using Python and PySpark.
  • Ingest data from multiple sources, including APIs, databases, flat files, and streaming platforms.
  • Monitor, troubleshoot, and enhance the performance of existing data pipelines.

About the company

Evnek logo

Evnek

Artificial Intelligence & Machine Learning Services

Evnek Technologies strives to be the leader in cloud and analytics services. The insights and quality services we deliver help build trust and confidence in our clients. We develop outstanding relationships with our clients and deliver on our promises. Moreover, we play a crucial role in challenging the traditional technologies and look for opportunities to innovate. Evnek Technologies specializes in Cloud and Enterprise Data Management. We offer services in data integration, business intelligence, data warehousing, architecture, modeling and analytics. We are thought leaders and work with the latest technologies in the Big Data, Cloud, and Data Science space. Evnek Technologies is passionate about adding value. We partner with our clients and ensure a positive user experience all the while building elegant and scalable solutions that evolve with the company and remain dynamic in an ever-changing business landscape.

Company details

IndustryArtificial Intelligence & Machine Learning Services
Company size11 - 50

Links

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Job description

Job Title: Junior Data Engineer

Experience: 2–4 Years 
Location: Remote / Hybrid 
Notice Period: Immediate Joiner

Job Summary

We are looking for a motivated Junior Data Engineer with 2–4 years of experience to join our growing data engineering team. The ideal candidate should have hands-on experience in building and maintaining data pipelines, working with cloud-based data platforms, and developing scalable ETL/ELT solutions. You will collaborate with senior data engineers, data analysts, and business stakeholders to deliver reliable and efficient data solutions.

Key Responsibilities

  • Develop, maintain, and optimize ETL/ELT pipelines for data integration and processing.
  • Build data processing applications using Python and PySpark.
  • Ingest data from multiple sources, including APIs, databases, flat files, and streaming platforms.
  • Write efficient, optimized, and scalable SQL queries for data transformation and reporting.
  • Monitor, troubleshoot, and enhance the performance of existing data pipelines.
  • Perform data quality validation and support data governance initiatives, including data lineage.
  • Work with Azure Data Factory, Azure Data Lake, and Azure Databricks to develop cloud-native data solutions.
  • Participate in Agile ceremonies, sprint planning, code reviews, and continuous improvement activities.
  • Collaborate with cross-functional teams to understand business requirements and deliver data solutions.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
  • 2–4 years of hands-on experience in Data Engineering.
  • Experience working with cloud platforms, preferably Microsoft Azure.
  • Strong understanding of data integration, transformation, and pipeline development.
  • Excellent SQL and analytical problem-solving skills.
  • Good communication and collaboration skills.
  • Ability to work independently as well as in a team-oriented Agile environment.

Preferred Skills

  • Exposure to streaming data processing frameworks.
  • Understanding of data warehousing concepts.
  • Knowledge of data governance and data quality practices.
  • Familiarity with DevOps practices and deployment automation.



Requirements


Required Technical Skills

  • Strong programming skills in Python
  • Proficiency in SQL for querying and data transformation
  • Hands-on experience with PySpark
  • Experience with Azure Data Factory (ADF)
  • Knowledge of Azure Data Lake
  • Basic working knowledge of Azure Databricks
  • Experience with Git version control
  • Basic understanding of Apache Kafka
  • Basic knowledge of CI/CD pipelines
  • Good understanding of ETL/ELT architecture and best practices




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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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