Lark Mullins
Husband. Father. Leader.
#data-engineering posts
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How Data Engineering Teams Can Empower Organizations
Technology teams, especially infrastructure, operations, and platform engineering are the backbone of modern organizations. These teams ensure the seamless operation of critical systems, enabling businesses to deliver reliabe and secure services. However, the complexity and demand of their roles require not just technical expertise but also an different leadership approach. Servant leadership, characterized by prioritizing the needs of the team and fostering growth, collaboration, and innovation, is proving to be a key aspect for success in engineering environments.
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A Guide to Building a Successful Data Engineering Team
Data engineering teams play a crucial role in today’s organizations, enabling the design, maintenance, and optimization of data infrastructure that supports analytics, machine learning, and strategic decision-making. Building a high-performing data engineering team involves more than just hiring talented individuals; it requires thoughtful team-building, fostering a supportive culture, implementing robust processes, and aligning efforts with business objectives.
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Designing and Implementing Data Engineering Pipelines in Kubernetes (AWS EKS)
Businesses need robust data pipelines to ingest, process, and analyze vast amounts of data efficiently. Kubernetes, particularly AWS Elastic Kubernetes Service (EKS), is a powerful platform for orchestrating these pipelines, offering scalability, reliability, and integration with cloud-native tools. This guide provides an in-depth look at planning, implementing, observing, and maintaining data engineering pipelines using Kubernetes, with hands-on Terraform and Python examples.