{"id":1759593,"url":"https://alion.io/job/n-ix-middle-data-analytics-engineer-2","title":"Middle Data Analytics Engineer","company":{"id":13248,"name":"N-iX","domain":"n-ix.com","url":"https://alion.io/company/n-ix","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":15,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-05T05:45:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ukraine"],"countries":["UA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":69000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":662},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"BigQuery","optional":true},{"name":"ClickHouse","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-09-08T09:01:40Z","employer_posted_date":"2026-09-17","last_verified_at":"2026-10-06T00:16:08Z","board_verified":true,"closed_at":null,"days_open":27,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":27},"description":"We are looking for a Middle Data Analytics Engineer to build reusable, production-grade pipelines that power our data deals, which are large-scale curated training sets for leading AI labs. You’ll ship engineering solutions with immediate revenue impact and collaborate with some of the world’s largest AI companies. \nResponsibilities:\nWork with the business development (BD) team, content experts, data science, and engineering teams to understand customer requirements and available metadata.\nMap customer requirements to our existing metadata and apply data modelling practices to maximize reusability and scalability\nBuild DBT models that are capable of querying up to 1B rows efficiently\nRefine DBT models based on visual QA to ensure accurate datasets at scale.\nPropose and implement automated solutions that streamline the curation process and increase scalability.\nServe as the engineering point of contact, partnering with Business Development to ensure accurate timelines, clear requirements, and manage all technical implementation pieces of the workflow\nAssist the expansion of the data curation workflow to accommodate data science approaches within DBT, streamline the review process to ensure a more rigorous statistical approach with more comprehensive testing\nRequirements:\nStrong SQL background with an understanding of query optimization and Snowflake experience.\nDBT experience preferred. \nGreat communication skills.\n3-5 years of experience in analytics/data engineering.\nPerform code reviews and collaborate with the team to create an optimized ecosystem.\nNice to have:\nBigQuery.\nPython.\nClickHouse.\nExperience delivering projects in an operational environment. \nInterest in data science to aid the understanding of customer use cases.\nInterest in photography, music and video creation.\nWe offer*:\nFlexible working format - 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