{"id":1581556,"url":"https://alion.io/job/magma-math-data-engineer","title":"Data Engineer","company":{"id":1888373,"name":"Magma Math","domain":"magmamath.com","url":"https://alion.io/company/magmamath","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Warsaw, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":24000,"max":31000,"currency":"PLN","period":"month","gross":null,"usd_annual":96864},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"Git","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Amazon EKS","optional":true},{"name":"ArgoCD","optional":true},{"name":"ClickHouse","optional":true},{"name":"GitHub","optional":true},{"name":"GitHub Actions","optional":true},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"Node JS","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-01T13:08:00Z","employer_posted_date":null,"last_verified_at":"2026-10-01T13:08:00Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Magma Math, is a K-12 platform that helps teachers make smarter instructional decisions and encourages deeper student-driven discussions and collaboration around math.\nWe're a fast-growing, well-funded company in the top tier of European EdTech - backed by $40M Series A and growing like crazy. But we're keeping it lean, smart, and fun - without the corporate fluff.\nOur work has a real impact: we're helping students around the world get better at math, and we're recognized by education experts for improving how math is taught and learned.\nWe're based in Warsaw, but our team spans New York , Stockholm , and London - and you'll have chances to meet everyone in person!\nOn-site role: We expect candidates to work from office 4 days a week.\nWhat we're looking for\n We are looking for a Data Engineer to build and own the pipelines that our product and business decisions depend on. You will work on both real-time streaming and batch workloads, from ingestion through to a modelled warehouse layer that analysts and services query directly.\nThis is a hands-on, infrastructure-close role. You will design pipelines, write the Terraform that provisions them, and stay responsible for them in production. If you like owning data end to end rather than picking up tickets on someone else's stack, this will suit you.\nWhat You'll Work With\nDesign, build and operate streaming pipelines with Kafka, Kinesis, Firehose and Flink\n\nBuild and maintain batch ETL/ELT pipelines into Redshift\n\nModel and evolve our data warehouse - identify the underlying business goals and architect accordingly\n\nWork with analysts, backend engineers and product to turn requirements into reliable, well-documented datasets\n\nManage all data infrastructure as code with Terraform on AWS (S3, Lambda, SQS, Kinesis, Firehose, Redshift)\n\nInstrument pipelines with monitoring, alerting and data quality checks so problems surface before stakeholders notice them\n\nTake part in code review and keep our engineering standards high\n\nMust Have\n2-3+ years of commercial experience as a Cloud Data Engineer\n\nApache Flink (Java or Python API) for stream processing\n\nStreaming platforms: Kafka and/or Kinesis, including practical understanding of partitioning, ordering, delivery guarantees and backpressure\n\nData warehouse architecture experience - you have designed a warehouse or a significant part of one, not only queried it\n\nExperience in a data-critical environment - where data accuracy, freshness or latency directly affects revenue, compliance or user safety (fintech, adtech, e-commerce at scale, healthcare, security, IoT or similar)\n\nStrong SQL, with hands-on experience in Amazon Redshift (query tuning, distribution/sort keys, workload management)\n\nAWS: S3, Lambda, SQS, Kinesis, Firehose, Redshift\n\nTerraform - you provision your own infrastructure\n\nGit and a collaborative branching/review workflow\n\nFamiliarity with agentic development - you use AI coding agents and LLM-based tooling as part of your daily workflow, and understand where to trust them and where to verify\n\nPython for data engineering - production-quality code, not just scripts\n\nNice To Have\nClickHouse\n\nNode.js\n\nApache Spark\n\nExperience with distributed architectures and their failure modes (consistency, partial failure, idempotency, exactly-once vs at-least-once)\n\nOur Stack\nClickHouse\n\nPython\n\nFlink\n\nKafka\n\nKinesis\n\nFirehose\n\nLambda\n\nSQS\n\nS3\n\nEKS\n\nTerraform\n\nArgoCD\n\nGitHub Actions\n\nQuick Suite\n\nGit\n\nWhat We Offer\nSalary up to 24,000 PLN/month (+VAT) depending on seniority\n\n26 days of leave covered by a yearly bonus\n\n10 days of paid sick leave\n\nYearly team meetups with all the people in company\n\nGreat Warsaw office - full floor just for us with snacks, drinks, and top-tier coffee\n\nMultisport Plus card\n\nTable football and chill board game nights with pizza & beer\n\nOccasional movie nights\n\nWe take your wellbeing very seriously - we want everyone to feel comfortable here\n\nRecruitment Process\n30-min intro call\n\nTechnical interview 2h (on site in office)\n\nCulture fit interview in office\n\nInterview with Product and Tech leaders\n\nReference check\n\nReady to make an impact?\nApply now and let's build something great together! Apply now and let's build something great together!","description_format":"text","description_chars":4232,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["E-learning","Virtual Events","Human Resources"],"lifecycle":[{"event":"open","at":"2026-10-01T13:25:12Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":17,"reasons":["seen:0","win:early","comp:junior"],"computed_at":"2026-10-02T02:57:31Z"},"pay":{"stated_usd_annual":96864,"is_top_pay":false},"html_url":"https://alion.io/job/magma-math-data-engineer","json_url":"https://alion.io/job/magma-math-data-engineer.json","meta":{"generated_at":"2026-10-02T02:57:31Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4010,"day_limit":5000,"remaining_today":990,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}