Senior Software Engineer (Data)

About the Company:

Stable Kernel is a technology services firm and custom software developer building scalable software solutions for cutting-edge, innovative enterprises to move their business forward. We are headquartered in Atlanta, GA.

We’re a privately held, Great Place to Work Certified Company™ with a multi-award-winning culture and an impressive 10-plus-year trajectory of sustainable growth. At Stable Kernel, we support our employees in ways that help them do some of the best work of their lives.

About the Role:

As a Stable Kernel Senior Software Engineer (Data), you play an essential role in setting our portfolio of world-class clients up for success through the development and delivery of their most innovative, transformational data initiatives. You will collaborate daily with other data engineers and a product owner to design, develop, and optimize scalable data pipelines that enable clients to extract actionable insights crucial to the health of their business. You have every opportunity to grow your skills and knowledge using a modern, feature-rich cloud-native data stack.. Your knowledgeable practice, reliability, and consultative nature make you a data engineer that stakeholders and teammates trust.

As a senior software engineer (data), you’ll take ownership of pipeline development and implementation, data model creation and refinement, and determine methods of extracting data from upstream data sources. You’ll own implementing system-wide data patterns compliant with architectural decision records and consistent with technologies in the data stack. 

Senior Data Engineers may be classified as individual contributors or people managers with individual contributor responsibilities.

Core Responsibilities Include:

• Technical Impact: 
• Design and implement robust data pipelines, with an eye to the growth of the product and team, improving the speed of future work and ensuring high data quality and contributing to DataOps/DevOps initiatives to ensure complete and timely data flows.
• Improve performance of data pipelines and data lake queries used by data analysts.
• Apply your firm grasp of the concepts and practices of data engineering in the areas of ingestion, transformation, serving with a strong awareness of system and project needs for security, data management, DataOps, Data architecture, orchestration and standard software engineering practices.
• Providing expert feedback that improves the overall delivery of work.
• Defending the work against compromise and corner-cutting.
• Designing test strategies and involving yourself in CI/CD and automated testing for high system reliability.
• Mentoring others in best practices.
• Ensuring a high standard of quality across the project. 
• Identifying, diagnosing, and resolving complex pipeline and data issues.
• Business Alignment: 
• Understanding the client's business and goals and using them to create and update roadmap issues.
• Identifying opportunities to provide additional value for our clients by suggesting and delivering improvements based on your observations.
• Contributing to the estimation of work for high-level planning and costing that clearly identifies gaps, risks, and assumptions.
• Interacting with Others:
• Coordinating with data stakeholders outside your team as necessary.
• Influencing your team’s roadmap.
• Advising people across the Director and VP-levels of the organization.
• Reporting status with a general understanding of where each member's work is.
• Autonomy & Ambiguity: 
• Designing and supporting long-term roadmaps with limited direction and requiring no direction on project plans.
• Considering and planning around cross-department dependencies to most effectively break down work across the team and solicit data product use cases and requirements.
• Working with ambiguity to define and break down challenging projects (e.g., projects that are hard to derive benefits from until the end of the project, projects that are very large, or projects that have a lot of uncertainty or require novel solutions).
• Problem-Solving:
• Analyzing the effectiveness of decisions and demonstrating accountability for outcomes.
• Making trade-offs between short-term and long-term solutions. 
• Evaluating trade-offs others are making.
• Anticipating, recognizing, and mitigating risks to prevent potential roadblocks. 
• Escalating issues and bringing recommended solutions to the table.
• Leadership:
• Taking ownership and contributing to process improvements tha