Director – Principal Engineer

Position Summary

Direct a team of engineers, analysts, and product managers through the planning, delivery, and operations of solutions to deploy world-class data solutions solving complex business problems.

Role and Responsibilities

Duties: Direct a team of engineers, analysts, and product managers through the planning, delivery, and operations of solutions to deploy world-class data solutions solving complex business problems. Work with business stakeholders, engineering, data science, platform teams, and business partners to evolve, deliver, and support the technology strategy and roadmaps of new and existing applications and platforms. Develop and participate in key strategic projects to drive company revenue. Manage technical team through the solution design process to define data and solutions requirements to meet business logic. Leverage and develop talent on the team through all phases of project efforts, including requirements gathering, assessment, and backlog refinements. Identify and utilize industry best practices to define engineering standards to build scalable, cost-efficient, quality solutions adherent to privacy. Manage vendors and contractors setting up data quality standards, best practices, and process efficiency to ensure quality deliverables. Lead the technical team to build sustainable data products and provide actionable insights to company stakeholders. Accountable for delivery of development and operational efforts by ensuring efforts are staffed, structured, budgeted, and prioritized appropriately.

Requirements: Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics or a related field and ten (10) years of progressive, post-baccalaureate experience as a Director – Principal Engineer or related occupation in data engineering and big data applications. The 10 years of experience must have included:

Experience in architecture design and development of largescale data platforms and data applications in cloud environments like AWS, GCP and Azure; Experience in building highly performant and scalable data ingestion pipelines, and hands-on experience with cloud-based big data technologies such as Spark, BigQuery, and Azure Data Lake Analytics. Experience in Hadoop SQL tools, including Hive and Presto; Monitoring, debugging and troubleshooting Azure, GCP and AWS cloud managed services, including Spark, EMR, DataProc, Composer (Airflow); Experience in metadata management, high availability, working on data problems at scale and suggesting efficient and reliable patterns to support wide variety of integration, including both batch and streaming; Managing multiple tasks simultaneously with a rigid determination to meet deadlines;

(7) Experience in programming languages such as Python, Scala, Java and C#;

(8) Experience in enterprise security protocols, building RESTful services, and best practices in cloud deployments; and

(9) Experience in continuous integration pipelines using DevOps.

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Skills and Qualifications

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