Senior Data Engineer

Company Profile: VLink, founded in 2006, is a leading global provider of software engineering services with next-gen technologies and best-in-class talent. Our Headquarters are in the U.S, and we have offices in 7+ countries from North AmericaEurope to APAC, with expansion plans in the Middle East. With over 1,000 employees working globally, VLink has helped SMBs, and large enterprises achieve their business goals, and gained the trust of Fortune-250 companies. VLink is ‘Great Place to Work® Certified™' and has been a consistent winner as- Best Places to Work in CT. Trust, collaboration, and accountability are the three elements that are at the core of VLink’s work culture. We value our professionals, providing comprehensive benefits and the opportunity for growth. Job Title: Senior Data Engineer/Architect Location: St Louis, Missouri, United States Duration: Long Term Job Description: Required qualifications to be successful in this role • Design various enterprise information and data and analytics strategies, including defining visions, conducting assessments of people, processes, and technology; and developing dynamic business value roadmaps. • Design and implement modern industry best practices in governance, management, and quality of information/data. • Design and implementation of data quality scorecards and metrics. • Evaluation, selection and implementation of tools and technology for data catalogs, data governance, data quality and data management. • Collaborate with business and technical teams to provide direction for and contribute to development, implementation and rollout of solutions and consulting services. Min Qualifications • At least 7 years of demonstrated experience with programming languages such as Python or Go; • Demonstrated experience migrating Python codebases to Go • Strong understanding of cloud-native security best practices • Strong understanding of DevOps best practices • Direct experience implementing service meshes (e.g., Istio) in Kubernetes environments • Strong understanding of Kubernetes architecture and concepts with direct experience deploying software using the Kubernetes control plane • A demonstrated understanding of Machine Learning and Generative AI concepts • Author high-quality Golang code to deliver new features, evolve existing services, and resolve defects • Familiarity with API design principles (REST, gRPC) and API gateway technologies • Demonstrated experience with programming languages such as Python or Go • Deep knowledge and demonstrated experience with Google Kubernetes Engine and Google Cloud Platform • Knowledge of key architectural patterns, such as microservices and event-driven architecture, with a deep understanding of their related trade-offs • Knowledge of best practices for Continuous Integration and Continuous Deployment (CI/CD) • Familiarity with data architecture and modeling concepts and paradigms • Familiarity with Observability concepts, such as Service Level Objectives (SLOs) and Service Level Indicators (SLIs), and related tooling (e.g., Datadog, OpenTelemetry, etc.) • Demonstrated experience as a productive reviewer of code, with an ability to coach others on the differentiation of style and correctness • Demonstrated experience with relational databases and declarative query languages such as SQL (e.g., Oracle, Postgres, etc.) • Experience with the git version control system and related tools such as GitHub or GitLab • Experience with Infrastructure as Code (IaC) tooling (e.g. Terraform, etc.) • Familiarity with the publish/subscribe models and supporting technologies (e.g., Apache Kafka, Google Pubsub, AWS SNS/SQS, etc.) • Proven experience in designing, building and running large-scale systems Desired Qualifications • At least 7 years of demonstrated experience with programming languages such as Python or Go; • Demonstrated experience migrating Python codebases to Go • Strong understanding of cloud-native security best practices • Strong understanding of DevOps best practices • Direct experience implementing service meshes (e.g., Istio) in Kubernetes environments • Strong understanding of Kubernetes architecture and concepts with direct experience deploying software using the Kubernetes control plane • A demonstrated understanding of Machine Learning and Generative AI concepts