Data/AI Engineer (Databricks, AWS, Python, AI))

Provides advanced data solutions by using software to process, store, and serve data to others. Tests data quality and optimizes data availability. Ensures that data pipelines are scalable, repeatable, and secure. Utilizes a deep dive analytical skillset on a variety of internal and external data.

Role Summary

The Data/AI Engineer is responsible for designing, developing, enhancing, and supporting scalable cloud-based data pipelines, data products, and data-driven applications. This is a hands-on engineering role requiring strong technical expertise in modern data engineering technologies, problem-solving abilities, and a product mindset to deliver reliable, secure, and high-quality data solutions.

The role requires the ability to work independently on assigned initiatives while collaborating closely with Technical Leads, Product Owners, Architects, Analysts, and other Engineering teams. The individual will contribute to the design, development, deployment, enhancement, and operational support of modern data platforms and data products that enable business outcomes and data-driven decision making.

In addition to delivering new capabilities, the Data/AI Engineer will be responsible for supporting existing data products and applications, performing production support activities, troubleshooting incidents, implementing enhancements, and driving continuous improvement. The individual is expected to take ownership of assigned deliverables from development through production support while seeking guidance from the Technical Lead for complex technical, architectural, or cross-functional decisions.

Responsibilities

• Build and optimize data ingestion, transformation, integration, and storage solutions supporting analytical and operational workloads.
• Design, develop, test, and maintain scalable batch and real-time data pipelines, data products, and cloud-based data solutions.
• Own assigned deliverables from design through deployment, ensuring quality, reliability, performance, security, and maintainability.
• Collaborate with Technical Leads, Product Owners, Architects, Analysts, and Engineering teams to translate business requirements into technical solutions.
• Implement data quality controls, monitoring, observability, automation, and CI/CD practices to improve platform reliability and engineering productivity.
• Support and enhance business-critical data products, applications, and platforms through defect resolution, performance improvements, and continuous modernization initiatives.
• Troubleshoot production issues, perform root-cause analysis, implement preventive actions, and contribute to operational excellence.
• Participate in application-support activities, release support, and production operations, including flexible working hours when required to support critical deliverables, production incidents, business commitments, or global stakeholders.
• Contribute to technical documentation, reusable components, engineering standards, and AI-assisted development practices that improve quality and delivery efficiency.
• Proactively identify risks, dependencies, and improvement opportunities while working independently with guidance from the Technical Lead when required.

Qualifications and Skills

• Bachelors degree in Computer Science, Information Technology, Engineering, Computer Applications, or a related discipline from a recognized institution.
• Minimum of 5 years of relevant experience with the majority of experience focused on Data Engineering.
• Hands-on experience designing, developing, and supporting scalable data pipelines, ETL/ELT frameworks, and cloud-based data solutions.
• Experience delivering data engineering solutions in cloud environments and Agile product teams.
• Demonstrated ability to independently deliver assigned workstreams while collaborating effectively with Technical Leads and Architects.
• Experience supporting production data platforms, data products, and business-critical applications.
• Strong understanding of software development lifecycle, production support, operational excellence, and continuous improvement practices.

Must have Skills

• Cloud Platforms- Hands-on experience with AWS data services such as S3, Glue, Lambda, Redshift, Athena, Step Functions, SNS/SQS, IAM, CloudWatch, and Kinesis, as relevant to the assigned solutions.
• Data Engineering- Strong experience with scalable ETL/ELT pipelines, data integration, batch processing, data tran…