{"id":1525228,"url":"https://alion.io/job/cricut-senior-data-engineer","title":"Senior Data Engineer","company":{"id":171160,"name":"Cricut","domain":"cricut.com","url":"https://alion.io/company/cricut","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":79,"open_postings":12,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":41,"computed_at":"2026-10-04T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["South Jordan, United States","Jordan"],"countries":["US","JO"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":116000,"max_usd":227000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":769},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"DynamoDB","optional":false},{"name":"Feature Store","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"A/B Testing","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Hudi","optional":true},{"name":"Apache Iceberg","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Embeddings","optional":true},{"name":"IAM","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-09-29T17:59:18Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-05T01:06:12Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Cricut® empowers people to make and personalize almost anything-from custom cards and apparel to everyday items and home décor. Our smart cutting machines, design apps, and materials make creativity easy and accessible for everyone. We believe everyone is born creative, and our mission is to put the power of handmade into the hands of all. With a passionate community of Makers around the world, Cricut helps turn inspiration into real, tangible creations-one project at a time.\nLet’s make.\n We're hiring a Senior Data Engineer to shape the data foundation behind Cricut's product analytics, personalization, and AI initiatives. You'll own and evolve our event data platform, from app instrumentation through streaming and batch ingestion to the warehouse. You'll also build the pipelines and feature infrastructure that feed our recommendation systems and machine learning models.\nThis role sits where data engineering meets ML. You'll work closely with product engineering, data science, ML engineering, analytics, and experimentation teams. Together you'll make sure our data is reliable, well-modeled, and ready for both decision-making and production models.\nWhat You'll Do\nDesign, build, and operate scalable batch and streaming pipelines on AWS using Airflow (MWAA), Glue, Kafka, S3, and Redshift\nLead the evolution of our product event platform, including schema design, event taxonomy, versioning, and migrations to next-generation event architecture\nBuild event data quality and observability: schema validation, instrumentation testing, anomaly detection, freshness and completeness monitoring, and lineage across pipelines\nHandle late-arriving and out-of-order data correctly, using lookback reprocessing and idempotent, incremental loads that keep business metrics accurate\nBuild and maintain the data foundations for personalization and recommendation systems, including the interaction, content, and project datasets used for model training and inference\nPartner with ML engineers to build feature pipelines and a batch plus low-latency feature store (for example, Redshift or S3 to DynamoDB) for real-time serving\nSupport ML workflows on AWS Batch and SageMaker, including training data generation, offline evaluation datasets, and delivery of model outputs to downstream APIs\nInstrument and model data for new AI-powered product experiences, including interaction, generation, and feedback events that close the loop on model improvement\nDevelop well-designed fact and dimension models that power BI, ad-hoc exploration, and experimentation platforms\nTune warehouse performance and cost through distribution and sort strategies, workload management, and efficient unload and serving patterns\nSet engineering standards for code review, testing, CI/CD, documentation, and on-call practices, and mentor other engineers\n 8+ years of experience in data engineering, including building and owning production pipelines at scale\nStrong SQL and Python skills; experience with PySpark or Spark is a plus\nDeep hands-on experience with AWS data services (S3, Glue, Redshift, DynamoDB, Lambda, IAM)\nProduction experience with Apache Airflow, including DAG design, dependency management, templating, alerting, and backfills\nExperience with streaming and event ingestion (Kafka, Kinesis, SQS, or similar) and clickstream or product analytics data\nStrong data modeling skills (dimensional and event modeling) and a clear sense of how data design affects downstream metrics\nA track record of building data quality and observability frameworks, not just pipelines\nExperience supporting ML systems in production: feature engineering, training datasets, feature stores, or model-serving data flows\nAbility to lead cross-functional technical work, write clear design documents, and turn ambiguous business needs into sound architecture\nClear communication with engineers, data scientists, and business partners alike\nNice to Have\nExperience with recommendation systems or personalization data (interaction logs, embeddings, candidate generation, ranking features)\nFamiliarity with SageMaker, AWS Batch, or MLOps tooling (model registries, experiment tracking, pipeline orchestration)\nExperience with analytics instrumentation tooling or tracking-plan governance\nExposure to LLM or generative AI applications, such as vector stores, retrieval pipelines, or evaluation and feedback data\nExperience with A/B testing platforms and experiment metric pipelines\nExperience with data lake table formats (Iceberg, Delta, Hudi) or Redshift data sharing\nA passion for making, crafting, or creative tools\nWhy You'll Love It Here\nYour work directly shapes how millions of makers discover, design, and create\nYou'll help build the data backbone for Cricut's AI and personalization roadmap\nYou'll have real ownership of platform architecture and a strong voice in technical direction\nYou'll join a collaborative team that values craft, curiosity, and impact\n We’ve Got You Covered\nAt Cricut, we take care of our people. Enjoy competitive Medical, Dental, and Vision coverage, a 401(k) match, generous PTO, tuition reimbursement, and a yearly lifestyle stipend to support your wellness and passions. You’ll also receive exclusive employee discounts-and best of all, you’ll be surrounded by some of the most talented, creative, and curious minds out there.\nA Quick Note Before You Apply…\nCricut is in an exciting chapter of transformation. We’re evolving fast-refining our strategy, growing our teams, and raising the bar across everything we do. This is an incredible opportunity for the right kind of person-but it’s not for everyone.\nWe’re looking for A-players-people who thrive in dynamic environments, turn challenges into momentum, and consistently deliver their best work. If that sounds like you, read on.\nHere’s what makes someone a great fit for this role (and for this moment at Cricut):\nYou move with urgency. You don’t wait for perfect clarity to act-you start, learn, and adjust.\nYou set high standards. You take ownership, deliver quality, and hold yourself accountable.\nYou stay focused when things move fast. You prioritize what matters most and tune out the noise.\nYou collaborate like a pro. You elevate others, communicate clearly, and bring a low-ego, high-output energy.\nYou embrace AI as part of your toolkit. From idea exploration to data analysis and creative problem-solving, you leverage AI to accelerate innovation and amplify impact-because technology and creativity go hand-in-hand here.\nOne More Thing (It’s a Big One)\nThis role is in-office at least 4-5 days per week. We believe real collaboration, innovation, and culture are built face-to-face. If you’re energized by working alongside smart, kind, creative people-and love those hallway conversations that spark the next great idea-you’ll feel right at home.\nIf you’re looking for a fully remote role, this may not be the right fit. But if you’re excited by challenge, purpose, and building something better-let’s make something amazing together.\nRelocation Statement:\nThis position is eligible for relocation assistance.\nWhat to Do Next: Please attach your resume, cover letter and/or include links to your portfolio or other social presence. If you want to show your super powers in other ways - include that information too. You can be sure that Cricut® is an employer who values individuality, equality and diversity, so tell us what you’re all about. If you are a Maker or a DIY enthusiast, whether you think you are a good one or not, we would love to hear about it when you send us your information.\nCricut® is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. This position is contingent on successfully completing a Criminal Background Check upon hire. 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