Vacancy expired!
The Data Engineer is responsible for building and maintaining enterprise-grade ETL, reporting and analytics solutions. They are responsible for ensuring the team is consistently delivering performant, secure, and efficient solutions. They act as an example to the team members, collaborate closely with customers, and remove or escalate roadblocks. Additionally, they apply their knowledge of business intelligence/ data architecture principles, data warehousing, data structures, and analysis as a daily contributor.
- Develop data architecture and ETL solutions using sound, repeatable, industry standard methodologies.
- Enhance existing data systems and optimizing ETL systems
- Lead development activities to migrate out of legacy technologies to cloud micro services driven Data Platform
- Communicate and maintain Master Data, Metadata, Data Management Repositories, Logical Data Models, Data Standards
- Create and maintain optimal data pipeline architecture by assembling large, complex data sets that meet functional / non-functional business requirements
- Work with business partners on data-related technical issues and develop requirements to support their data infrastructure needs
- Build industrialized analytic datasets and delivery mechanisms that utilize the data pipeline to deliver actionable insights into sales volume, products efficiency and other key business performance metrics
- Contribute to architectural design and foster new ideas and innovations in our products
- S. or M.S. in computer science or a related field, with academic knowledge of computer science (algorithms, data structures etc.) and 5 or more years of experience, or equivalent combination of education and or experience
- 7+ years of coding experience with SQL, ETL, Data Warehouse, Data Modeling, Data Engineering with a willingness and ability to learn new ones
- 3+ years of experience in building highly scalable ETL or DataOps pipelines including AWS (Glue etc.) or open source data technologies
- 3+ years of experience in applying principles, best practices, and trade-offs of schema design to various types of database technologies, including relational, columnar, graph, SQL, or NoSQL
- 1+ years of experience with database, data lake, and data mesh architecture designs with structured and unstructured data
- 1+ years of experience with implementing web services, including SOAP and RESTful APIs using micro services architectures and design patterns
- Experience in implementing batch and real-time data integration frameworks and applications, in private or public cloud, including AWS or Azure, using various technologies, including Spark, Impala, debugging, identifying performance bottlenecks, and fine tuning those frameworks
- Knowledge of relational and dimensional modeling techniques
- Proficient with Python and knowledgeable with AT LEAST ONE of the following programming languages: C#, Java, Go, JavaScript, TypeScript, or R.
- Experience with BI tools such as Power BI, Sisense, Tableau, SSRS
Vacancy expired!