- Passionate to learn
- High sense of ownership
- Able to work in a fast-paced and deadline-driven environment
- Loves technology
- Highly skilled at data interpretation
- Problem solver
Skills to work in a challenging, complex project environment
- Naturally curious and have a passion for understanding consumer behavior
- High level of motivation, passion, and sense of ownership
- Excellent communication skills to manage an incredibly diverse slate of work, clients, and team personalities
- Proficient in multi-tasking, ability to to work on multiple projects in a deadline-driven fast-paced environment
- Proven ability to work in ambiguity and manage chaos
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and datasets.
- 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.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- 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:
- Big data: Hadoop, Spark, Kafka, etc.
- Relational SQL and NoSQL databases, including Postgres and Cassandra.
- Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- AWS cloud services: EC2, EMR, RDS, Redshift
- Stream-processing systems: Storm, Spark-Streaming, etc.
- Object-oriented/ object function scripting languages: Python, Java, Scala, etc.
Project Delivery skills
- 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 infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies
- Build analytics tools that utilise 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/or 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 centres 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.
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