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Data Engineer

Data Engineer

Magma ConsultancyKakinada, IN
1 day ago
Job description

Location :  Remote

Type :  Part-time (20–25 hours per week)

About the Role

We are seeking a skilled  Data Engineer  to support our growing data operations on a part-time basis. The ideal candidate has hands-on experience in building, optimizing, and maintaining data pipelines and architectures. You’ll work closely with analysts, developers, and business teams to ensure reliable, efficient, and scalable data systems.

Key Responsibilities

  • Design, develop, and maintain  ETL / ELT pipelines  to collect, process, and store data from multiple sources.
  • Build and optimize  data models and warehouse structures  for analytics and reporting.
  • Ensure  data quality, integrity, and security  across all stages of the data lifecycle.
  • Collaborate with stakeholders to understand data requirements and provide scalable solutions.
  • Automate repetitive processes to improve performance and reliability.
  • Monitor, troubleshoot, and resolve issues within data workflows and integrations.

Required Skills & Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or related field.
  • 2–4 years of experience  in data engineering, data architecture, or a related role.
  • Proficiency in  SQL  and one or more programming languages (Python preferred).
  • Hands-on experience with  data pipeline tools  (e.g., Airflow, dbt, Luigi).
  • Experience with  cloud platforms  such as AWS, Azure, or GCP.
  • Knowledge of  data warehousing  (e.g., Snowflake, BigQuery, Redshift).
  • Understanding of  APIs, JSON, REST, and data integration techniques.
  • Familiarity with  version control (Git)  and CI / CD workflows.
  • Preferred (Nice to Have)

  • Experience with  data visualization tools  (Power BI, Tableau, Looker).
  • Exposure to  machine learning pipelines  or data lake architectures.
  • Prior experience in a  part-time or remote setup .
  • What We Offer

  • Flexible working hours (ideal for professionals balancing other commitments).
  • Remote-first environment with collaborative tools.
  • Opportunity to work with modern data technologies.
  • Supportive and growth-focused team culture.
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