Data Engineer

Design and Build Data Solutions • Design, develop, and maintain scalable batch and near real-time data pipelines using SQL and Python. • Build, optimize, and support data ingestion, transformation, and orchestration processes in Snowflake and AWS. • Develop reusable data assets, curated datasets, and data models that support analytics, reporting, operational workflows, and AI solutions. • Create and maintain ETL/ELT frameworks to integrate data from multiple source systems. • Ensure data solutions are scalable, reliable, secure, and cost-effective. Cloud Data Engineering • Leverage AWS services such as S3, Lambda, Glue, ECS, and other cloud-native technologies to enable enterprise data processing and storage. • Support cloud data warehouse and data lake architectures. • Monitor, tune, and optimize data workloads to improve performance, reliability, and cost efficiency. • Understand data quality, governance, lineage, and observability capabilities across data products and platforms. AI Enabled Engineering Productivity • Leverage AI powered development tools and coding assistants to improve engineering productivity, accelerate software delivery, and enhance code quality. • Utilize generative AI capabilities to support code generation, documentation creation, testing, troubleshooting, and data pipeline development. • Identify opportunities to automate manual engineering processes through AI-enabled workflows and tooling. • Evaluate and adopt emerging AI technologies and best practices while adhering to enterprise security, governance, and responsible AI standards. DevOps & Engineering Excellence • Utilize GitLab for source control, CI/CD pipelines, automated testing, code reviews, and deployment automation. • Implement DevOps best practices to improve delivery speed, quality, reliability, and operational support. • Participate in production support, incident management, root cause analysis, and continuous improvement activities. • Develop and maintain technical documentation, standards, and reusable engineering components. Agile Delivery & Collaboration • Participate in Agile Scrum ceremonies including sprint planning, backlog refinement, daily standups, sprint reviews, and retrospectives. • Collaborate with cross-functional teams to translate business requirements into scalable technical solutions. • Contribute to architecture, data modeling, and design discussions.