Galent · 6 hours ago
Principal Data Engineer
Galent is seeking a Principal Data Engineer to deliver high-impact technology solutions that shape the future of digital transformation. The role involves providing technical leadership, collaborating with various teams to implement data strategies, and driving data quality and best practices across the organization.
Responsibilities
Provide product technical leadership for teams to both analyze and take charge of long-term opportunities, designing a cutting-edge data solution and help with core development when needed
Act as Product Technical Lead
Act as subject matter expert for data domain within the IT organization and work with business to author self-service data products
Collaborate with leaders, business analysts, project managers, IT architects, technical leads, and other developers, along with internal customers and cross functional teams to implement data strategy
Design and build data engineering pipeline frameworks while ensuring these are reusable, scalable, efficient, maintainable, gracefully recover from failures, reprocessing the data should be easy
Drive data quality, best practices, coding standards, Test Driven Development, identifying single source of truth for data across systems and Quality Analytics (Mean Time to Recover, Mean Time between Failures, Patterns causing failures)
Utilize data pipelines to provide actionable insights into data quality and product performance
Identify, design, and implement internal process improvements such as automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability
Contribute to the continuous improvement of data engineering across the enterprise by researching industry best practices and determining best usage of specific cloud services and tools
Work with data squads to ensure data products are designed with privacy and compliance baked in (Privacy by design)
Work with product teams to help prioritize team objectives and initiatives/team features
Conduct road shows on the data products across the organization
Advocate the agile process and test-driven development, using data engineering development tools to analyze, model, design, construct and test reusable
9+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale applications in data analytics, warehousing, and data engineering
Working experience in data analytics (data wrangling, mining, integration, analysis, visualization, data modeling, analysis/analytics, and reporting)
Should have at least 5 years of experience in optimizing Spark jobs for performance and cost-efficiency using advanced techniques such as partitioning, caching, cluster configuration tuning, and troubleshooting bottlenecks
Qualification
Required
10+ years of experience
Provide product technical leadership for teams to both analyze and take charge of long-term opportunities, designing a cutting-edge data solution and help with core development when needed
Act as Product Technical Lead
Act as subject matter expert for data domain within the IT organization and work with business to author self-service data products
Collaborate with leaders, business analysts, project managers, IT architects, technical leads, and other developers, along with internal customers and cross functional teams to implement data strategy
Design and build data engineering pipeline frameworks while ensuring these are reusable, scalable, efficient, maintainable, gracefully recover from failures, reprocessing the data should be easy
Drive data quality, best practices, coding standards, Test Driven Development, identifying single source of truth for data across systems and Quality Analytics (Mean Time to Recover, Mean Time between Failures, Patterns causing failures)
Utilize data pipelines to provide actionable insights into data quality and product performance
Identify, design, and implement internal process improvements such as automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability
Contribute to the continuous improvement of data engineering across the enterprise by researching industry best practices and determining best usage of specific cloud services and tools
Work with data squads to ensure data products are designed with privacy and compliance baked in (Privacy by design)
Work with product teams to help prioritize team objectives and initiatives/team features
Conduct road shows on the data products across the organization
Advocate the agile process and test-driven development, using data engineering development tools to analyze, model, design, construct and test reusable
9+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale applications in data analytics, warehousing, and data engineering
Working experience in data analytics (data wrangling, mining, integration, analysis, visualization, data modeling, analysis/analytics, and reporting)
Should have at least 5 years of experience in optimizing Spark jobs for performance and cost-efficiency using advanced techniques such as partitioning, caching, cluster configuration tuning, and troubleshooting bottlenecks
Company
Galent
Galent is an AI-native digital engineering firm at the forefront of the AI revolution, dedicated to delivering unified, enterprise-ready AI solutions that transform businesses and industries.
Funding
Current Stage
Late StageCompany data provided by crunchbase