At the heart of our Data Solutions team are our super talented, highly-technical Data Engineers. Data Engineers are data experts who dive right into new client projects and make it their job to understand how a client’s data fits together and what that data means.
Utilizing this knowledge and the industry’s newest technologies (Aunsight, Hadoop, Docker, etc.), they create data lakes (fed by real-time data streams) that become the very foundation of the work we do. Critical at all stages of the data science process, Data Engineers work cross-functionally with both external and internal teams – from business analysts to data scientists; mobile app developers to platform engineers; IT teams to high-level executives. Data Engineers also provide valuable feedback to our software team that helps to shape the development of Aunsight, our proprietary end-to-end cloud analytics platform; and the development of our proprietary mobile app, Sightglass.
The best Data Engineers are patient, persistent, focused, creative, and incredibly curious. They love to learn and seek out opportunities to identify unexpected solutions or develop alternate ways to solve challenging problems.
Essential Duties & Responsibilities:
- Build and own “one source of truth” data sets to facilitate consistency and efficiency in extracting and analyzing data from disparate data sources.
- Ensure data integrity by developing and executing necessary processes and controls around the flow of data.
- Innovate and improve efficiency of managing data to allow for greater speed and accuracy of producing analyses, metrics, and insights.
- Collaborate with internal and external teams to understand business needs/issues, troubleshoot problems, conduct root cause analysis, and develop cost effective resolutions for data anomalies.
- Provides input into data governance initiatives to enhance current systems, ensure development of efficient application systems, influence the development of data policy, and support overall corporate and business goals.
- Utilizes technology to analyze data from applicable systems to review data processes, identify issues, and determine actions to resolve or escalate problems that require data, system, or process improvement.
- Verifies accuracy of table changes and data transformation processes. Test changes prior to deployment as appropriate.
- Recommend and implement enhancements that standardize and streamline processes, assure data quality and reliability, and reduce processing time to meet client expectations.
- Communicate progress and completion to project team. Escalate roadblocks that may impact delivery schedule.
- Stay up-to-date on data engineering and data science trends and developments.
- Follow company policy and procedures which protect sensitive data and maintain compliance with established security standards and best practices.
- Additional duties as assigned to ensure client and company success.
- Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or related field, or 3 plus years of relevant work experience..
- Experience working with relational database structures, SQL and/or flat files and performing table joins, web crawling, and web development..
- Proficiency in one or more of the following programming languages: PHP, Java, or Python and a familiarity with Node.js.
- Natural curiosity about what’s hidden in the data through exploration, attention to detail, and ability to see the big picture – similar to putting together a 10,000-piece puzzle.
- Resourceful in getting things done, self-starter, and productive working independently or collaboratively—ours is a fast-paced entrepreneurial environment with performance expectations and deadlines.
- Ability to learn quickly and contribute ideas that make the team, processes, and solutions better.
- Ability to communicate your ideas (verbal and written) so that team members and clients can understand them.
- Ability to defend your professional decisions and organize proof that your ideas and processes are correct.
- Share our values: growth, relationships, integrity, and passion.
- Experience working in one of the following industries: healthcare, financial services, media, or manufacturing.
- Experience working with commercial relational database systems such as electronic medical records or other clinical systems, customer relationship management software, or accounting systems.
- Familiar with various data management methodologies, data exploration techniques, data quality assurance practices, and data discovery/visualization tools.
- Prior experience supporting business intelligence operations, managing technical, business, and process metadata related to data warehousing.
- Experience working with NoSQL, Hive, MapReduce and other Big Data technologies is preferred but not required.
Willing to train the right candidate.
- Experience working with distributed and/or parallel systems experience or knowledge of concepts.