We are looking for a Data Engineer to join our growing team of analytics experts. The hire 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. 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. 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.
- Analyzing, interpreting, and monitoring the geological formation data to ascertain the extraction risks and the best methods of extraction.
- 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 analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Create data for other department members that assist them in building and optimizing our product into an innovative industry leader.
- Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs
Requirements and Skills
- The ability to manage a physically demanding and stressful work environment.
- Technical expertise with data models, data mining, and segmentation techniques.
- 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 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.
- The candidate must have 5+ years of experience in a Data Engineer role and 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 relational SQL and NoSQL databases, including Postgres and MySQL.
- Experience with data pipeline and workflow management tools: FME, SSIS, Python, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Snowflake.
- Experience with object-oriented/object function scripting languages: Python, Java, etc.
- Strong technical, analytical, numerical, and critical thinking skills.