As a savvy Data Engineer you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams, regionally, and with global and cross brand collaboration.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. Reporting to the Senior Director of Consumer, Sales & Marketing (IT) they must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company's data architecture to support our next generation of products and data initiatives.
- Ensures high-quality access to data sources.
- Responsible for controlling data and the quality of its use (referencing, standardization and qualification) in order to facilitate its exploitation by teams (Data Analysts and Data Scientists).
- Assist with specification of the data policy and the structuring of its life cycle in compliance with existing regulations, in co-operation with the Chief Data Officer. The Data Engineer/Steward, scope of intervention is focused on application systems in the data management and processing domain, and on platforms such as Google Cloud Platform, Azure, other cloud solutions, Multi-Cloud, Big Data, IoT, etc.
- Responsible for overseeing and integrating data of a variety of types originating from these different sources, and for confirming the quality of the data entering the Data Lake (receives data, deletes duplicates, etc.) Articulation of data, data structures and principals to both IT and business stakeholders in nontechnical terms will be essential for stakeholder management.
DATA MANAGEMENT: Day-to-Day
Captures the data (structured and unstructured) produced in different applications or
outside the entity
- Integrates the elements - Structure the data (semantics, etc.)
- Responsible for Mapping the available elements
- Cleans the data through automation (elimination of duplicates,...)
- Validates the data structures and identifies exceptions (automates solutions , ML, AI)
- Creates the data repository and/or recommends expansion of framework
- Data Privacy principals and directives (privacy by design methodology), working knowledge of GDPR, CCPA, etc.
Create and maintain optimal data pipeline architectures
- 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 using ‘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.
- Keeping data separated and secure across national boundaries through multiple data centers and 'Cloud' 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.
Experience & Qualifications:
- 5 years of experience in similar Data Engineer/Steward like role
- Advanced knowledge and experience working with databases, query authoring as well as working familiarity with common languages.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes, 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.
- Strong project management and organizational skills.
- 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 Google Cloud Platform cloud services & platform
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.