Location
Ontario, CA | United States
Job description
Central Label Management - Data Engineer
Job Description
- Create and maintain optimal data pipeline architecture.
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data
- delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
- data sources using SQL and AWS 'big data' technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition,
- operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related
- technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our
- product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Work with system integration and middlewares (MuleSoft, Talend, Solace and etc)
- Perform proof of concept with customer in data integration and data load
- Managing structure and unstructured data set
- Managing and design data privacy, integrity and security solution
- Managing data with high confidentiality, integrity and privacy
Skills
- Experience with working in agile methodologies (Scrum or SAFe)
- Good teamwork and communication skill (Higher Performance Team)
- Able to be self organized and focus in delivering values to the business
- Always work with integrity, passion and courage
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) and Nosql unstructured database
- Familiarity with a variety of databases (Microsoft SQL is mandatory).
- Experience building and optimizing 'big data' data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores. Preferable middleware knowledge, example: MuleSoft, Solace.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate
- degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Job tags
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