Senior Data Engineer

Position Summary

We are seeking an experienced Senior Data Engineer to help design, build, and optimize modern cloud-based data platforms that transform data into actionable insights. In this role, you will collaborate with data engineers, data scientists, architects, product managers, and business stakeholders to develop scalable, reliable, and high-performance data solutions that support analytics, artificial intelligence, machine learning, and business intelligence initiatives.

The ideal candidate has strong experience building enterprise data platforms, designing scalable data models, and developing cloud-native data pipelines using modern data engineering technologies.

Key Responsibilities

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  Design, develop, and maintain scalable, reliable, and efficient data pipelines.

  
  


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  Create conceptual, logical, and physical data models that support enterprise analytics and reporting.

  
  


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  Design and optimize database structures using dbt and implement data transformation pipelines that support high-performance analytics.

  
  


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  Collaborate with data engineers, data scientists, architects, and cross-functional teams to deliver scalable data solutions.

  
  


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  Develop and maintain cloud-native data pipelines using technologies such as AWS (S3, Lambda, SNS, SQS), Apache Iceberg, Snowflake, dbt, and Airflow.

  
  


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  Participate actively in Agile/Scrum ceremonies and contribute to continuous improvement initiatives.

  
  


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  Partner with product managers, architects, and engineering teams to deliver enhancements to enterprise data platforms.

  
  


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  Establish and maintain standards and best practices for data pipeline development, naming conventions, configuration management, and documentation.

  
  


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  Ensure data platforms meet service level agreements (SLAs) for reliability, scalability, performance, and data quality.

  
  


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  Support data governance initiatives, including data contracts, metadata management, and documentation.

  
  


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  Engage with business stakeholders to understand evolving data requirements and prioritize enhancements that improve business value.

  
  


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  Maintain comprehensive technical documentation to support operational excellence, governance, and long-term maintainability.

  
  

Required Qualifications

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  5+ years of experience designing and developing enterprise data pipelines.

  
  


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  Strong understanding of data modeling principles, including dimensional modeling and data normalization.

  
  


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  Proficiency in at least one modern programming language, such as Python.

  
  


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  Advanced SQL skills with the ability to analyze and optimize complex datasets.

  
  


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  Hands-on production experience with workflow orchestration platforms such as Apache Airflow.

  
  


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  Experience working with Snowflake or similar cloud data warehouse technologies.

  
  


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  Experience with cloud platforms, preferably AWS, including services such as S3, Lambda, SNS, and SQS.

  
  


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  Experience working with modern data lake technologies such as Apache Iceberg or equivalent open table formats.

  
  


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  Strong understanding of data transformation frameworks such as dbt.

  
  


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  Experience implementing data governance best practices, including data contracts and metadata management.

  
  


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  Strong analytical, algorithmic, and problem-solving skills.

  
  


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  Excellent written, verbal, and interpersonal communication skills.

  
  


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  Understanding of OLTP and OLAP database architectures and their appropriate use cases.

  
  


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  Ability to thrive in a fast-paced, collaborative, and Agile development environment.

  
  


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  Self-motivated with a strong attention to detail and a commitment to delivering high-quality solutions.

  
  


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  Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience.

  
  

Preferred Qualifications

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  Experience building enterprise-scale cloud data platforms supporting analytics, AI, and machine learning workloads.

  
  


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  Experience implementing CI/CD pipelines and DevOps best practices for data engineering.

  
  


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  Knowledge of data governance, lineage, observability, and data quality frameworks.

  
  


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  Experience working with large-scale distributed data environments and cloud-native architectures.

  
  


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  Familiarity with modern software engineering practices, version control systems, and automated testing.

  
  


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  Experience collaborating with cross-functional teams across engineering, analytics, product, and business organizations.

  
  

• Total years of exp - 9-13 years


• 5+ years of Strong experience with Core Data Platform/Data Engineering


• Data Modeling (Dimensional Modeling, Normalization, OLTP vs. OLAP)


• Python for data engineering and automation


• Advanced SQL (complex queries, optimization, performance tuning)


• Snowflake (hands-on implementation and optimization)


• Understanding of OLTP vs. OLAP architectures and data warehouse design


• Job stability is mandatory