Data & Platform Engineering

Synopsis

The ideal candidate is an experienced data pipeline builder and data wrangler and utilizes the latest technology to implement and support platforms for analytical use-cases. The selected candidate 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. 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. Also will be responsible for monitoring analytical systems to ensure that the environments run smoothly.

Accountabilities

• Evaluate business needs and objectives
• Identify opportunities for data acquisition
• Analyze and organize raw data
• Create and maintain optimal data pipeline architecture,  Interpret trends and patterns / Build algorithms and prototypes
• 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 SQL and  ‘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.

Education & Experience

• Candidate with 3-8 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.
• Technical expertise with data models, data mining, and segmentation techniques
• Strong analytic skills related to working with unstructured datasets.
• Experience building and optimizing data pipelines, architectures and data sets.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Ability to troubleshoot and solve complex problems.
• Basic understanding of UNIX batch/shell scripting, Database SQL.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.