Senior Data Engineer

The Team

We are seeking a Senior Data Engineer to join American Tower’s IT organization’s Data & Analytics team. The team focuses on building, maintaining, and optimizing cloud-native data pipelines and datasets that enable analytics, reporting, and artificial intelligence at scale. Day to day you will collaborate with Data Products, Analytics, and Business teams across Global Operations, Finance, and Sales to deliver reliable and scalable data solutions within the enterprise data platform and engineering standards defined by platform leadership. As a Senior Data Engineer, you will contribute to advancing automation, platform maturity, and intelligent data operations.

What You Can Offer Us

• Build and maintain scalable, production-grade data pipelines across ingestion, transformation, storage, and serving layers in a cloud environment.    
• Design and implement reusable data components and frameworks that improve reliability, consistency, and developer productivity.    
• Apply data modeling techniques, including dimensional and domain-oriented modeling, to support analytics, reporting, and operational use cases.    
• Implement data quality checks, validation rules, and monitoring to ensure trustworthy and reliable data assets.    
• Follow established engineering standards including coding practices, testing, version control, documentation, and continuous integration and continuous delivery.    
• Optimize pipeline performance and cost through efficient query design, partitioning, and resource utilization.    
• Troubleshoot production data issues, perform root cause analysis, and support incident response and resolution.    
• Collaborate with Data Products, Analytics, and Business teams to translate requirements into scalable data solutions.    
• Other duties as assigned.   

What You Need to Succeed

• Bachelor’s degree required, with a concentration in Computer Science or a related quantitative field preferred.
• Master’s degree in Computer Science and/or a related quantitative field preferred.
• Between 4–7 years of data engineering or data platform experience required.
• Strong proficiency in Structured Query Language and Python, with hands-on experience in Spark or PySpark for large-scale data processing.
• Experience working with cloud platforms such as Azure and modern data platforms such as Databricks and/or Snowflake.
• Hands-on experience building, deploying, and maintaining pipelines in production environments.
• Experience with streaming or near real-time data processing, such as Kafka and/or event-driven architectures.
• Experience building reusable frameworks, metadata-driven pipelines, and/or shared platform components.
• Exposure to data governance concepts such as lineage, metadata, access control, and compliance.
• Exposure to automation and intelligent data workflows, including early experience with agent-based and/or control-plane patterns.
• Familiarity with orchestration tools such as Airflow or Azure Data Factory.
• Fluency in English required; multilingual capabilities preferred.
• Strong written and oral communication skills, including the ability to present ideas and suggestions clearly and effectively.
• Ability to work with different functional groups and levels of employees to effectively and professionally achieve results.
• Strong organizational skills; ability to accomplish multiple tasks within the established timeframes through effective prioritization of duties and functions in a fast-paced environment.