{"id":3453754,"url":"https://alion.io/job/pulserise-technologies-senior-data-engineer-python-airflow-dbt-gcp","title":"Senior Data Engineer (Python / Airflow / dbt / GCP)","company":{"id":4485907,"name":"PulseRise Technologies","domain":"pulserisetechnologies.io","url":"https://alion.io/company/pulserise-technologies","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Ukraine"],"countries":["UA"],"hiring_countries":["DE","FR","AT","BE","BG","HR","CY","CZ","DK","FI","HU","IE","IT","NL","PL","RO","ES","SE","EE","GR","LV","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":27,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":63000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Beautiful Soup","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"Playwright","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"Scrapy","optional":false},{"name":"Selenium","optional":false},{"name":"Google BigQuery","optional":true}],"status":"live","first_seen_at":"2026-10-27T21:22:37Z","employer_posted_date":null,"last_verified_at":"2026-10-27T21:22:37Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We are looking for a Senior Data Engineer to own the data platform of a fast-growing startup, from architecture all the way to production. The company helps investors and other teams find and research companies, so reliable, fresh and well-structured data is at the heart of the product. Today the platform processes data one job at a time in containers. You will lead its move to running many jobs at once, with event-driven data intake and orchestrated batch workflows. Your daily work will combine Python, Airflow, dbt, GCP and PostgreSQL with large-scale web scraping from many sources. You will also solve hard data problems, such as matching company and people records across sources and using LLMs to pull structured data out of text. This role suits someone who likes building from zero, enjoys owning a wide area, works well on their own and is comfortable in a fully remote team with no fixed working hours.\n\nDetails:\n\nSchedule: Full time\n\nLocation: Remote – EU \n\nStart: ASAP\n\nDuration: Long-term\n\nEnglish: Fluent\n\nType of collaboration: B2B Contract\n\nAbout the project:\n\nThe client is a startup building a data platform that helps investors and other teams find and research companies. The platform collects data from many sources, cleans it, links related records and turns it into useful insights about companies. As the product grows, the current one-at-a-time processing needs to become a faster, event-driven system that handles many jobs at once. The Senior Data Engineer will lead this change and own the whole platform, from design to day-to-day running. The team is small, so engineers own a wide area and have a direct impact on the product. The company works fully remotely, and you don't need to overlap with anyone's working hours.\n\nYou have:\n\nExperience building a production data platform with many data sources from zero, including its architecture, deployment and day-to-day running\n\nProduction experience with workflow orchestration tools (Airflow, Dagster, Prefect or Temporal)\n\nHands-on experience with dbt and Google Cloud Platform (GCP)\n\nStrong Python skills, including asynchronous HTTP and concurrent processing\n\nHands-on web scraping experience (Scrapy, Playwright, Selenium or Beautiful Soup)\n\nStrong PostgreSQL skills: data modeling, query optimization and reliable incremental loading\n\nExperience with event-driven architecture, including retries, failure recovery and dead-letter queues\n\nComfort working fully remotely and on your own, with no fixed hours that overlap with the team\n\nFluent English\n\nNice to have:\n\nExperience in startups or small engineering teams where you owned a wide area\n\nEntity resolution experience, especially matching and reconciling company and people records across sources\n\nExperience using LLMs to extract structured data or enrich data\n\nFamiliarity with BigQuery and Dataform\n\nBackground in company, investment or B2B data platforms\n\nWhat to do:\n\nOwn the data platform from start to finish, from architecture to production and day-to-day running\n\nLead the move from one-at-a-time container processing to concurrent, event-driven data intake and orchestrated batch workflows\n\nBuild and maintain data pipelines with Python, Airflow, dbt and GCP\n\nBuild and scale web scraping that runs across many sources at once, handling rate limits and failures\n\nDesign PostgreSQL data models, optimize queries, and set up reliable incremental loads, idempotent upserts and backfills of historical data\n\nBuild solid failure recovery, retries and dead-letter handling for event-driven data intake\n\nMatch and reconcile company and people records 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