Senior AWS Data Engineer

🕒 April 27

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 44%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Mactores

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2008

💼 Consulting

🏢 Enterprise

Consulting • Enterprise • Data

Mactores is a company that provides end-to-end data platform solutions aimed at accelerating business value through automation. Since 2008, Mactores has been helping businesses with digital transformation, offering services like Enterprise Data Lakes, Scalable Databases, Modern Data Warehouses, Automated DataOps, MLOps, and Generative AI solutions. They focus on enabling faster and cost-effective migrations and modernizations in data analytics, partnering with leading platforms to drive innovation and success. Mactores works alongside tech teams to strategize and implement the right data solutions timely and efficiently.

📋 Description

• Develop and maintain data pipelines using Amazon EMR or Amazon Glue. • Create data models and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. • Build and maintain the orchestration of data pipelines using Airflow. • Collaborate with other teams to understand their data needs and help design solutions. • Troubleshoot and optimize data pipelines and data models. • Write and maintain PySpark and SQL scripts to extract, transform, and load data. • Document and communicate technical solutions to both technical and non-technical audiences. • Stay up-to-date with new AWS data technologies and evaluate their impact on our existing systems.

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field. • 3+ years of experience working with PySpark and SQL. • 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue. • 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto. • 1+ years of experience building and maintaining the orchestration of data pipelines using Airflow. • Strong problem-solving and troubleshooting skills. • Excellent communication and collaboration skills. • Ability to work independently and within a team environment.