Data Engineer

Location: 100% Remote
Expenses Allowed: No
Equipment/VDI Access: Yes

• Experience with relational database management systems (Oracle, Microsoft SQL Server)

• Familiarity with at least one commonly used programming language

• Knowledge of Software Development Life Cycle (SDLC) and best practices

• Data wrangling experience using a variety of tools and languages

• Strong proficiency in SQL

• Strong technical writing and presentation skills

• Data visualization experience using business intelligence tools such as Tableau, D3.js, R/Shiny, or SAP products

• Familiarity with project management workflow tools such as JIRA or Trello

• Experience with lean-agile principles and frameworks for project completion

• Capability to design and document conceptual, logical, and physical data models for relational and dimensional databases

• Ability to interpret process performance outputs and improve workflow performance

• Familiarity with modern source/version control tools such as Git, CodeCommit, or Subversion

• Familiarity with various raw data source types and how to interpret them (e.g., Unstructured JSON/BSON, flat files, XML, etc.)

• Experience with scripting languages such as R and Python

• Experience interacting with and extracting data from modern web APIs

• Experience working with cloud platforms such as AWS and Snowflake

Responsible for designing, configuring, developing, testing, and deploying ELT/ETL processes and self-service reporting assets to enable data exploration capabilities for end users. The role involves proactive communication with data consumers to optimize performance, designing and building data models, and supporting enterprise architectural standards.
Additional duties include data cleansing, profiling, and tracing data quality issues to their source. The position provides operational and ad-hoc support for data systems, participates in data governance initiatives, and collaborates in Agile ceremonies. The Data Engineer works independently while also mentoring less-experienced team members.

• Design, configure, develop, test, and deploy ELT/ETL processes across multiple sources, targets, and tools.

• Develop self-service reporting assets to empower end users with data exploration capabilities.

• Demonstrate deep understanding of data domains, their generation processes, and potential biases.

• Communicate with data consumers to improve process performance and share best practices.

• Build and maintain collaboration across teams to deliver reliable data and insights.

• Provide operational, troubleshooting, and maintenance support for data warehouses, datasets, and pipelines.

• Offer on-call support for data platforms, reporting assets, and ETL processes.

• Design and implement data model structures and coach junior team members in best practices.

• Apply organizational standards and SDLC best practices to ensure high-quality data assets.

• Ensure compliance with regulations concerning sensitive data such as PHI and PII.

• Lead data cleansing and profiling efforts to maintain data accuracy and integrity.

• Participate in data governance activities and manage data assets effectively.

• Develop and support CI/CD pipelines under the guidance of senior engineers.

• Actively engage in Agile/scrum ceremonies, capturing and grooming user stories and features.

• Continuously grow business and technical acumen while supporting knowledge sharing within the team.

• Bachelor s Degree required; Master s Degree preferred

• 5 10 years of relevant experience in data engineering or related field