{"id":25927,"url":"https://alion.io/job/stable-kernel-principal-data-engineer","title":"Principal Data Engineer","company":{"id":6911,"name":"Stable Kernel","domain":"stablekernel.com","url":"https://alion.io/company/stable-kernel","size_band":"51-200","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":null,"currency":"USD","period":"year","gross":null,"usd_annual":170000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Pandas","optional":false},{"name":"Polars","optional":false},{"name":"Pulumi","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"Apache Iceberg","optional":true},{"name":"AWS Step Functions","optional":true},{"name":"dbt","optional":true}],"status":"live","first_seen_at":"2025-03-03T15:40:28Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-13T18:20:58Z","board_verified":true,"closed_at":null,"days_open":620,"trust":{"level":"stale","repost_count":1,"flags":["stale"],"days_open":619},"description":"About the Company:\nStable 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.\nWe’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.\n\nAbout the Role:\nAs a Stable Kernel Principal Data Engineer, 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 initiatives. You will collaborate daily with other engineers and product team members, make decisions that influence the path of a product roadmap, leverage software development best practices, and become a more well-rounded engineer as you learn new technologies. Your knowledgeable practice, reliability, and consultative nature make you an engineer that stakeholders and teammates trust.\nPrincipal Data Engineers may be classified as individual contributors or people managers with individual contributor responsibilities.\n\nCore Responsibilities Include:\nTechnical Impact: \nDesigning and implementing exemplary solutions regarding scalability and cost-effectiveness by making trade-offs between opportunity and complexity.\nSetting standards for codebase health and promoting best practices throughout the organization. \nBusiness Alignment: \nClarifying strategic outcomes and influencing roadmaps and projects.\nIdentifying, suggesting, and driving improvements in your customers' end-to-end experience.\nAiding in estimating work for new business with more unknowns and coaching others in estimation best practices. \nInteracting with Others: \nCoordinating across the entire company.\nInfluencing the entire organization to make changes to support your work.\nAdvising teams across the company.\nAutonomy & Ambiguity: \nDesigning a long-term roadmap with no direction. \nTranslating customer and business needs and strategic direction into projects and consistently simplifying high-complexity situations.\nCoaching and mentoring others in tackling ambiguity.\nProblem-Solving:\nDecomposing strategic direction into projects:\n Planning, communicating, and executing to solve our most challenging problems.\nEnsuring alignment with long-term objectives, fostering a culture of informed decision-making and innovation.\nAnticipating most risks and driving simplification to mitigate risks ahead of time. \nEscalating issues while solving them in parallel ensuring others are informed.\nLeadership:\nProposing new organization-level processes to improve key areas such as team throughput, employee happiness, or product engagement.\nDriving best practices across the organization.\nExhibiting exceptional mentoring abilities and fostering a culture of continuous learning and improvement by\nidentifying and nurturing potential in others \nproviding strategic guidance\nhelping develop career paths for team members \nLeading projects.\nSetting the strategic direction for projects or areas of technology, leading multiple project teams, and influencing decision-making at higher organizational levels. \nExhibiting strong capabilities in stakeholder management, negotiating, and problem-solving in complex scenarios. \nMentoring and developing other leaders within the team, fostering a culture of innovation, and contributing significantly to organizational goals.\n\nIntimate, Working Familiarity With:\nPython & Modern Programming Languages: Architect and deliver scalable data platforms using Python, with proficiency in at least one additional language such as Go, Java, C#, or Scala.\nData Processing Frameworks: Design and optimize high-volume data pipelines using DataFrame processing libraries such as Pandas or Polars.\nServerless Cloud Architecture: Build and operate cloud-native data solutions using AWS Lambda or equivalent serverless technologies.\nSoftware Engineering Best Practices: Apply modern software engineering principles to deliver production-quality, maintainable, testable, and observable code.\nDistributed Data Processing: Design and implement scalable ETL/ELT pipelines using AWS Glue, Apache Spark, PySpark, or similar distributed processing frameworks.\nData Modeling: Architect relational and analytical data models, including dimensional modeling, Star Schema, and Snowflake Schema to support reporting and analytics.\nInfrastructure as Code: Automate cloud infrastructure using Infrastructure as Code tools such as Terraform, Pulumi, or similar technologies.\nCI/CD for Data Platforms: Design and maintain CI/CD pipelines that automate the build, testing, deployment, and monitoring of data engineering workflows.\n\nGeneral Requirements:\n10+ years of development experience.\nExtensive experience serving as a trusted consultant to stakeholders and cross-functional teams, providing expert guidance on backend service design, delivery, and integration.\nA curious technologist who explores AI augmented development workflows, leveraging tools such as Anthropic models, Cursor, Copilot with Open Spec, Spec Kit, and related frameworks.\nDegree in Computer Science or relevant field or experience. \n\nNice to Haves:\nExperience building high-performance data services using Go (Golang).\nFamiliarity with Apache Iceberg for managing large-scale analytical datasets.\nExperience orchestrating complex workflows using AWS Step Functions.\nKnowledge of Slowly Changing Dimensions (SCD) and Change Data Capture (CDC) patterns for modern data architectures.\nExperience with data governance and cataloging platforms such as Unity Catalog, AWS DataZone, Apache Atlas, or dbt metadata.\nFamiliarity with columnar data formats including Parquet, ORC, and Avro for optimized analytical workloads.\nUnderstanding of OLTP and OLAP architectures and the appropriate use cases for each.\nAdditional experience implementing cloud infrastructure using Terraform, Pulumi, or similar Infrastructure as Code tools.\n\nA Bit More Info:\nMinimum Base Compensation: $170,000\nThis is a full-time position.\nStable Kernel operates a People Before Place Hybrid model, allowing most employees to choose where they can do their best work most days.\nMinimal travel is associated with this role.\nOur generous total compensation package includes:\nCompany-subsidized health, vision, and dental plan premium options beginning on the first day of employment\n401k with above-average company matching \nFully paid Group Life, Short and Long Term Disability, and AD&D insurance\nOptional Flexible Spending Account and Health Savings Account participation\nVoluntary Life, Critical Illness, and Accident insurance\nEAP and Health Advocacy program available at no cost to employees and their dependents\n$3000+ annual industry educational budget \nPaid time off and paid holidays Access to Perks at Work program featuring a variety of discounted products and services\n\n*Note - We are not sponsoring employment visas at this time. If you are currently in possession of an employment visa, it will need to be effective for at least 3 years from the date of your application for your candidacy for employment to be considered.\n\nStable Kernel’s culture is inclusive and expansive. We celebrate diversity in its many glorious forms and do not discriminate based on race, religion, color, national origin, gender role orientation, sexual orientation, age, marital status, veteran status, or disability status.\nHowever, we will discriminate against those unwilling to comply with the practice of our company values:\nwe work with integrity always\nwe respect our work and each other\nwe are dedicated to life-long learning and sharing\nwe stay hungry for new challenges\nIf you are like-minded in this regard, we hope you will apply. 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