Big Data Engineer

We’re looking for a Big Data Engineer who can find creative solutions to tough problems. As a Big Data Engineer, you’ll create and manage our data infrastructure and tools, including collecting, storing, processing and analyzing our data and data systems. You know how to work quickly and accurately, using the best solutions to analyze mass data sets, and you know how to get results. You’ll also make this data easily accessible across the company and usable in multiple departments.

Big Data Engineer Roles and Responsibilities:

• Gather and process raw data at scale.
• Design and develop data applications using selected tools and frameworks as required and requested.
• Read, extract, transform, stage and load data to selected tools and frameworks as required and requested.
• Perform tasks such as writing scripts, web scraping, calling APIs, write SQL queries, etc.
• Work closely with the engineering team to integrate your work into our production systems.
• Process unstructured data into a form suitable for analysis.
• Analyze processed data.
• Support business decisions with ad hoc analysis as needed.
• Monitoring data performance and modifying infrastructure as needed.
• Define data retention policies.

Big Data Engineer Skills/Requirements:

• 2 – 7 years of recent experience in data engineering.
• Bachelor’s Degree or more in Computer Science or a related field.
• A solid track record of data management showing your flawless execution and attention to detail.
• Strong knowledge of and experience with statistics.
• Programming experience, ideally in Python, Spark, Kafka or Java, and a willingness to learn new programming languages to meet goals and objectives.
• Experience in C, Perl, Javascript or other programming languages is a plus.
• Knowledge of data cleaning, wrangling, visualization and reporting, with an understanding of the best, most efficient use of associated tools and applications to complete these tasks.
• Experience in MapReduce is a plus.
• Deep knowledge of data mining, machine learning, natural language processing, or information retrieval.
• Experience processing large amounts of structured and unstructured data, including integrating data from multiple sources.
• Experience with machine learning toolkits including, H2O, SparkML or Mahout
• A willingness to explore new alternatives or options to solve data mining issues, and utilize a combination of industry best practices, data innovations and your experience to get the job done.
• Experience in production support and troubleshooting.
• You find satisfaction in a job well done and thrive on solving head-scratching problems.