Senior Software Engineer - Python and ETL

Role Overview: Join a world-class team of skilled engineers at Gartner IT who design, implement, and maintain innovative digital solutions to support colleagues and clients. As a Senior Software Engineer specializing in Python and ETL, you will have the opportunity to make a significant impact by delivering cutting-edge technology solutions that power Gartner. The organizational culture values nonstop innovation, an outcome-driven approach to success, and the belief that great ideas can come from anyone on the team. Key Responsibilities: - Design, implement, and maintain cloud-based, scalable, and resilient data pipelines to support batch workloads. - Architect high-performance, optimized data solutions by participating in requirements review, system design, and technical implementation. - Design, build, and automate data pipelines and applications for data scientists, analysts, and researchers to facilitate analytics, reporting, and experimentation. - Develop AI/ML-enabled data pipelines utilizing platforms like AWS Bedrock, SageMaker, and associated services. - Evaluate technical feasibility of proposed solutions, define implementation plans, identify risks and dependencies, and propose mitigation strategies. - Ensure all data solutions adhere to security, privacy, and compliance standards, and continually enhance pipelines to address evolving security requirements. - Collaborate with administrative and platform teams to support provisioning, configuration, monitoring, and maintenance of AWS services, SageMaker environments, and Postgres databases. - Lead automation efforts across the data analytics team using Infrastructure as Code (IaC), configuration management, CI/CD pipelines, and deployment best practices. - Work with Quality Assurance teams to design and implement automated testing frameworks to ensure data integrity, accuracy, and prevention of data loss. - Drive operational excellence by enhancing monitoring, alerting, logging, and observability of data pipelines. - Identify and integrate new cloud technologies, evaluating tools that enhance organizational capabilities and reduce the total cost of operation. - Collaborate with stakeholders to identify and develop reusable components, shared frameworks, and standards that enhance engineering productivity and consistency. - Act as a technical advisor for data engineering initiatives, influencing architectural decisions and best practices. - Provide regular project status updates to engineering leadership and stakeholders, highlighting progress, risks, and dependencies. - Contribute to documentation of architectures, pipelines, operational runbooks, and best practices to ensure long-term maintainability and knowledge sharing. Qualifications Required: - Bachelors degree or foreign equivalent degree in Computer Science, Information Systems, Engineering, or a related technical field, with 4-6 years of related work experience. - Excellent problem-solving and communication skills. - Proficiency in data architecture, data quality, Python, SQL, Spark, and data processing frameworks (preferably DBT). - Experience with AWS services such as S3, ECS, Lambda, EMR, Glue, and Step Functions; unit testing, reviews, and modern Big Data Modeling techniques. (Note: Additional details of the company were not provided in the job description.) Role Overview: Join a world-class team of skilled engineers at Gartner IT who design, implement, and maintain innovative digital solutions to support colleagues and clients. As a Senior Software Engineer specializing in Python and ETL, you will have the opportunity to make a significant impact by delivering cutting-edge technology solutions that power Gartner. The organizational culture values nonstop innovation, an outcome-driven approach to success, and the belief that great ideas can come from anyone on the team. Key Responsibilities: - Design, implement, and maintain cloud-based, scalable, and resilient data pipelines to support batch workloads. - Architect high-performance, optimized data solutions by participating in requirements review, system design, and technical implementation. - Design, build, and automate data pipelines and applications for data scientists, analysts, and researchers to facilitate analytics, reporting, and experimentation. - Develop AI/ML-enabled data pipelines utilizing platforms like AWS Bedrock, SageMaker, and associated services. - Evaluate technical feasibility of proposed solutions, define implementation plans, identify risks and dependencies, and propose mitigation strategies. - Ensure all data solutions adhere to security, privacy, and compliance standards, and continually enhance pipelines to address evolving security requirements. - Collaborate with administrative and platform teams to support provisioning, configuration, monitoring, and maintenance of AWS services, SageMaker environments, and Postgres databases. - Lead automation efforts across the data analytics team using Infrastructur