LABUR
Lead Data Engineer
LABUR, Saint Paul, Minnesota, United States, 55199
Overview
As a Lead Data Engineer, you will operate in a crucial role focused on evolving our data infrastructure. This person will lead the design, implementation, and continuous enhancement of data architectures, data pipelines, and interfaces to maximize scalability and efficiency, and spearhead the development of data solutions that are synchronized with our strategic objectives. This hands-on leadership role involves mentoring senior data engineers and fostering a culture of excellence and proactive growth. You will collaborate extensively with data scientists, BI teams, software engineers, and business stakeholders to devise and execute effective data engineering strategies that drive significant business impact.
ResponsibilitiesSpearhead the architectural design and optimization of robust, scalable data pipelines using SQL, Python, and cloud-based ETL tools such as Databricks. Oversee data flow and processing to support large-scale operations and ensure system-wide efficiency.Oversee the development and refinement of complex data models to accurately align with critical business processes, ensuring seamless integration with comprehensive data architecture, including Big Data frameworks like Spark.Shape and enhance data architecture strategy, making high-level decisions on data storage, consumption, integration, and management across cloud platforms (Azure, AWS, or Google Cloud).Facilitate Agile/SCRUM frameworks to drive efficient project delivery. Oversee sprints and stand-ups, implementing these methodologies to optimize development processes across teams.Spearhead collaboration efforts with data scientists, BI teams, and engineering groups to translate intricate data requirements into executable engineering strategies. Serve as a key technical liaison among stakeholders.Guide senior data engineers and technical team leads, fostering best practices in SQL, Python, and cloud technologies while establishing a culture of excellence and continuous advancement.Create and enforce the highest data quality standards and governance policies, ensuring reliability and regulatory compliance across all data operations.Monitor and refine the performance of data infrastructure, identifying and resolving high-level bottlenecks or inefficiencies in cloud and Big Data environments.Lead the evaluation and strategic implementation of innovative tools and practices that enhance our capabilities.Oversee the creation of detailed documentation for data processes, pipelines, and architectures, ensuring clarity, consistency, and easy maintenance across technical teams.Provide support for existing legacy data solutions and develop migration paths to new platforms as required.
QualificationsBachelor’s Degree in Computer Science, Data Science, Information Technology, or other quantitative disciplines such as Science, Statistics, Economics, or Mathematics. Master’s Degree preferred.10+ years of progressive experience in data engineering, with proven expertise in designing, implementing, and leading initiatives for optimizing databases and data pipelines.Extensive hands-on experience with SQL Server, Oracle, or other RDBMS.Advanced skills in SQL and Python for complex data manipulation and analytics.Experience with leadership around data modeling and architecture for both analytics and transactional systems within large-scale environments.At least 2-4 years of experience leading teams of data engineers with a demonstrated ability to mentor and guide teams in the development and optimization of data systems.Expertise with at least one major cloud data platform (Azure, AWS, Google Cloud) with extensive application in data engineering projects.Deep knowledge of Big Data technologies such as Spark and Cloud ETL tools like Databricks, with a focus on scalability and real-time processing capabilities.Skilled in developing data models for integration and analysis that support complex business intelligence and data analytics initiatives.Ability to articulate complex data concepts and project updates clearly to both technical and non-technical stakeholders.Robust knowledge of developing and managing ETL and ELT architectures using various tools and frameworks.Experience with cloud platforms such as Azure, AWS, or Google Cloud, and their respective data services and tools.Understanding of Big Data technologies and frameworks, including Spark and Cloud ETL tools such as Databricks.Knowledge of Agile methodologies and SCRUM practices, capable of integrating these into project management and daily workflows.Knowledge of data quality standards and governance, ensuring data integrity and compliance across all processes.Collaboration skills with the ability to work effectively with cross-functional teams, including data scientists, BI analysts, and software engineers, to implement data solutions.Mentorship and Leadership skills with experience mentoring junior engineers and leading project teams to promote knowledge sharing and professional growth within the team.Ability to work independently.
Preferred CertificationsProfessional certification in Agile and SCRUM methodologies.Certifications in Python and SQL programming (e.g., Microsoft Certified: Python Programming Specialist, Oracle SQL Certification).Certifications in cloud services relevant to the job (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate).Big Data certifications (e.g., Cloudera Certified Professional (CCP): Data Engineer, Databricks Certified Professional Data Scientist).
#J-18808-Ljbffr
As a Lead Data Engineer, you will operate in a crucial role focused on evolving our data infrastructure. This person will lead the design, implementation, and continuous enhancement of data architectures, data pipelines, and interfaces to maximize scalability and efficiency, and spearhead the development of data solutions that are synchronized with our strategic objectives. This hands-on leadership role involves mentoring senior data engineers and fostering a culture of excellence and proactive growth. You will collaborate extensively with data scientists, BI teams, software engineers, and business stakeholders to devise and execute effective data engineering strategies that drive significant business impact.
ResponsibilitiesSpearhead the architectural design and optimization of robust, scalable data pipelines using SQL, Python, and cloud-based ETL tools such as Databricks. Oversee data flow and processing to support large-scale operations and ensure system-wide efficiency.Oversee the development and refinement of complex data models to accurately align with critical business processes, ensuring seamless integration with comprehensive data architecture, including Big Data frameworks like Spark.Shape and enhance data architecture strategy, making high-level decisions on data storage, consumption, integration, and management across cloud platforms (Azure, AWS, or Google Cloud).Facilitate Agile/SCRUM frameworks to drive efficient project delivery. Oversee sprints and stand-ups, implementing these methodologies to optimize development processes across teams.Spearhead collaboration efforts with data scientists, BI teams, and engineering groups to translate intricate data requirements into executable engineering strategies. Serve as a key technical liaison among stakeholders.Guide senior data engineers and technical team leads, fostering best practices in SQL, Python, and cloud technologies while establishing a culture of excellence and continuous advancement.Create and enforce the highest data quality standards and governance policies, ensuring reliability and regulatory compliance across all data operations.Monitor and refine the performance of data infrastructure, identifying and resolving high-level bottlenecks or inefficiencies in cloud and Big Data environments.Lead the evaluation and strategic implementation of innovative tools and practices that enhance our capabilities.Oversee the creation of detailed documentation for data processes, pipelines, and architectures, ensuring clarity, consistency, and easy maintenance across technical teams.Provide support for existing legacy data solutions and develop migration paths to new platforms as required.
QualificationsBachelor’s Degree in Computer Science, Data Science, Information Technology, or other quantitative disciplines such as Science, Statistics, Economics, or Mathematics. Master’s Degree preferred.10+ years of progressive experience in data engineering, with proven expertise in designing, implementing, and leading initiatives for optimizing databases and data pipelines.Extensive hands-on experience with SQL Server, Oracle, or other RDBMS.Advanced skills in SQL and Python for complex data manipulation and analytics.Experience with leadership around data modeling and architecture for both analytics and transactional systems within large-scale environments.At least 2-4 years of experience leading teams of data engineers with a demonstrated ability to mentor and guide teams in the development and optimization of data systems.Expertise with at least one major cloud data platform (Azure, AWS, Google Cloud) with extensive application in data engineering projects.Deep knowledge of Big Data technologies such as Spark and Cloud ETL tools like Databricks, with a focus on scalability and real-time processing capabilities.Skilled in developing data models for integration and analysis that support complex business intelligence and data analytics initiatives.Ability to articulate complex data concepts and project updates clearly to both technical and non-technical stakeholders.Robust knowledge of developing and managing ETL and ELT architectures using various tools and frameworks.Experience with cloud platforms such as Azure, AWS, or Google Cloud, and their respective data services and tools.Understanding of Big Data technologies and frameworks, including Spark and Cloud ETL tools such as Databricks.Knowledge of Agile methodologies and SCRUM practices, capable of integrating these into project management and daily workflows.Knowledge of data quality standards and governance, ensuring data integrity and compliance across all processes.Collaboration skills with the ability to work effectively with cross-functional teams, including data scientists, BI analysts, and software engineers, to implement data solutions.Mentorship and Leadership skills with experience mentoring junior engineers and leading project teams to promote knowledge sharing and professional growth within the team.Ability to work independently.
Preferred CertificationsProfessional certification in Agile and SCRUM methodologies.Certifications in Python and SQL programming (e.g., Microsoft Certified: Python Programming Specialist, Oracle SQL Certification).Certifications in cloud services relevant to the job (e.g., AWS Certified Solutions Architect, Google Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate).Big Data certifications (e.g., Cloudera Certified Professional (CCP): Data Engineer, Databricks Certified Professional Data Scientist).
#J-18808-Ljbffr