Lead, Data Engineer
Magic Leap is seeking a Data Engineer professional. The Lead Data Engineering will support data warehouse, data analysis initiatives and ensure optimal data and information delivery architecture to support ongoing projects. The incumbent must be self-directed and comfortable supporting the data engineering and Business intelligence needs of multiple teams, systems and products. He/She will be reforming the company’s data architecture to support our next generation of products and data initiatives. In addition, this role will evaluate new or existing programs, maintenance, improvement, and support the business application solutions for internal business functions, which are based on the requirements and needs of such client base.
- Create and maintain optimal data pipeline architecture
- Integrate large, complex data sets that meet business requirements
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
- Evaluate/Review/Implement/Build the infrastructure required for optimal extraction, transformation, and loading of data from various data sources
- Work with stakeholders at multiple levels to assist with data-related technical issues and support their data infrastructure needs
- Support data analysis tools used by multiple business intelligence resources throughout the organization
- Work with data and analytics experts to strive for greater functionality in the data ecosystem
- Advanced working SQL knowledge and experience working with relational databases and working familiarity with a variety of databases
- Experience building and optimizing big data pipelines, architectures, and data sets
- Experience performing root cause analysis on internal & external data and processes and identify opportunities for improvement.
- Strong analytic skills related to working with both structured and unstructured datasets
- Build processes supporting data transformation, data structures, metadata, governance, and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
- Experience with relational SQL and NoSQL databases: Redshift, Snowflake, PostgreSQL, SQL Server
- Experience with data pipeline and workflow management tools: Informatica, Dell Boomi, or DataStage.
- Experience with business intelligence systems: Tableau and Paxata
- Experience with governance platforms: Alation and Collibra
- Experience with scripting languages: Python and Java
- Experience with big data tools: Hadoop, Spark, Hive, Impala, Scala.
- Track record of building design patterns, best practices and data architecture standards
- Experience in working with functional teams in Product Engineering, Supply Chain, Finance, Sales and People functions
- Capable of managing multiple priorities and meeting closely-spaced, ambitious timelines;
- Outstanding written and verbal communication skills;
- Additional qualification of SAP Certification in Sales and/or technical areas is highly beneficial
- Education and/or Experience: Bachelor's degree (B.A.) from four-year college or university in Engineering, Information Systems, Statistics, Informatics, Computer Science or or another quantitative field with 6+ years of experience in a Data Engineering role.
All your information will be kept confidential according to Equal Employment Opportunities guidelines.