{"id":2499150,"url":"https://alion.io/job/kendago-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3011695,"name":"Kendago","domain":"kendago.com","url":"https://alion.io/company/kendago","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Comeet","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Kiryat Ono, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":73000,"max_usd":188000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Django","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Redshift","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"ETL/ELT","optional":true}],"status":"live","first_seen_at":"2026-10-14T02:06:23Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T09:06:59Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Description\nKendago is on a mission to redefine how consumers go from noticing a need to buying the right solution online. In an internet shaped by AI, fragmented attention, and constantly shifting platforms, we build, own, and scale top-performing brands and offers - both our own and those of leading partners - by combining proprietary technology, data-driven decision making, and creative excellence at performance scale.\nWe operate at consumer scale, reaching millions of people every day across paid channels, owned funnels, and digital touchpoints. In a world where creative trends, consumer behavior, and platform algorithms shift overnight, Kendago stays ahead of the curve.\nWe move fast, think deeply, and build with purpose. Our culture is rooted in entrepreneurship, innovation, and collaboration - along with shared wins, team dinners, and a whole lot of good food and laughter.\nWe’re a team of doers, and boundary-breakers - product, data, R&D, growth, and creative talent who own the full stack of how consumer brands are built and scaled today. After 17 years in the game, every funnel, every test, every brand decision happens in-house - which means your work moves the needle directly and visibly. If you’re ready to tackle meaningful challenges, grow at lightning speed, and help shape the next frontier of consumer brand building, you belong here.\nABOUT THE ROLE\nWe are looking for a Senior Data Engineer with strong Python expertise and extensive experience building large-scale, distributed data systems.\nYou will play a key role in developing our next-generation data platform, building integrations with external data sources, and designing the services and pipelines that collect, process, and serve large volumes of data across our product.\nYou will own systems throughout their full lifecycle - from system design and hands-on development to deployment, scalability, and production monitoring - while contributing to technical decisions and working closely with the team on building reliable, high-performance data solutions.\nOur Office is located in Kiryat Ono.This is a hybrid position, including two work-from-home days per week, with flexibility .\nRequirements\n5+ years of professional software/data engineering experience, with strong hands-on Python proficiency.\nProven experience building and maintaining large-scale, data-intensive systems in production.\nStrong SQL skills, including working with large and complex datasets, query optimization, and data modeling.\nHands-on experience designing and developing data pipelines and services that process data asynchronously or in batches.\nSolid understanding of distributed-system fundamentals, including failure handling, retries, idempotency, concurrency, and eventual consistency.\nExperience contributing to system design and technical decisions around scalable, reliable data systems.\nExperience building and consuming REST APIs and integrating with third-party systems. Experience with FastAPI, Django, Flask, or similar frameworks is an advantage.\nStrong problem-solving skills and the ability to investigate unfamiliar systems and complex data flows.\nAbility to work independently, take ownership, make sound engineering decisions, and collaborate effectively within a small, highly technical team.\nAdvantage\nExperience working in FinTech, E-commerce, AdTech, or other high-scale data environments.\nExperience working with high-volume data processing and distributed data infrastructure.\nNice to Have-\nExperience with Amazon Redshift or another analytical data warehouse.\nFamiliarity with Docker, CI/CD, logging, monitoring, and troubleshooting production systems\nExperience building ETL or ELT pipelines and implementing data-quality checks.\nExperience with queues, schedulers, or workflow orchestration tools.\nFamiliarity with infrastructure as code and cloud infrastructure management.\nExperience with high-volume data ingestion, analytics platforms, marketing technology, or campaign-management systems.\nResponsibilities\nBuild and improvedata-collection and processing workflows, including scheduled, asynchronous, and long-running workloads.\nDevelop reliable integrations with external APIs, platforms, and data providers.\nDesign, build, and maintain backend services using Python and FastAPI.\nContribute to our new platform and capabilities such as algorithm execution and data collection orchestration.\nDesign efficient data models and queries for operational databases and analytical systems such as Amazon Redshift.\nHandle real-world integration challenges including rate limits, retries, partial failures, idempotency, and changing external schemas.\nImprove the performance, scalability, observability, and reliability of existing services.\nOwn features end to end: technical design, implementation, testing, deployment, monitoring, and ongoing improvement.\nCollaborate with product and engineering colleagues to turn ambiguous 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