{"id":1195591,"url":"https://alion.io/job/hofer-data-engineer-databricks-pyspark-sql","title":"Data Engineer (Databricks, PySpark, SQL)","company":{"id":1045017,"name":"Hofer KG","domain":"hofer.at","url":"https://alion.io/company/hofer-2","size_band":null,"is_staffing_agency":false,"is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Budapest, Hungary"],"countries":["HU"],"hiring_countries":["HU"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":49000,"max_usd":112000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":404},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Unix","optional":false},{"name":"pySpark","optional":true},{"name":"ServiceNow","optional":true}],"status":"live","first_seen_at":"2026-09-06T02:00:00Z","employer_posted_date":"2026-09-06","last_verified_at":"2026-09-24T18:41:01Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"PLACE OF WORK\n1112 Budapest, Boldizsár utca 2.\nAREA OF EMPLOYMENT\nIT\nSTART OF WORK\nas soon as possible\nEMPLOYMENT TYPE\nFull-time\n\nmegállapodás szerint\n\nMy responsibilities:\nDesign, develop, optimize, and maintain squad-specific data architectures and pipelines in line with ETL and data lake principles\nPrepare, align, and hand over data architecture and pipeline artefacts to the platform team for reuse across squads\nSolve complex technical data challenges that support business objectives\nDevelop data products for analytics, data scientists, and ML engineers to improve productivity within the team and across the organization\nAdvise, mentor, and support data and analytics professionals on data standards and best practices within the squad and organization\nContribute to the evaluation of emerging tools in data engineering and data science, helping to define and improve standards and ways of working\nDrive continuous improvement by contributing to training, capability development, and enhancements in analytical data engineering practices, standards, and processes\nThe knowledge I own:\nDegree in Computer Science or related field\n10+ years of experience in software or infrastructure development, including at least 4 years in data engineering within distributed computing, big data, or advanced analytics environments\nStrong expertise in SQL and data analysis, with proficiency in at least one programming language such as Python or Scala\nExperience in database development and data modeling, ideally with Databricks/Spark and SQL Server; knowledge of relational, NoSQL, and cloud-based databases.\nSolid understanding of distributed computing concepts, preferably with Spark or MapReduce\nHands-on experience with Azure tools such as Azure Data Factory, Azure Databricks, Event Hub, Synapse, and ML services\nGood understanding of data and analytics concepts, including dimensional modeling, ETL, data warehousing, reporting, data governance, and handling structured and unstructured data\nFamiliarity with Unix systems, especially shell scripting\nBasic knowledge of network concepts, connectivity, and troubleshooting\nFoundational understanding of machine learning, data science, AI, statistics, or applied mathematics\nStrong communication skills and fluent English; German is a plus\nTech Stack\nAzure Databricks\nAzure Data Factory\nPython\nPySpark\nServiceNow\nM365\nand other tools depending on the role.\nThe offer that would convince me:\nWe develop and maintain our own product with high emphasis on quality and long-term stability\nCode quality matters: we follow Clean Code and SOLID principles backed by robust testing\nFlexible working hours and remote work options\nCompetitive salary with regular adjustments based on inflation and loyalty\nAccess to continuous learning via our internal learning platform and expert communities\nOnline application:\nPlease use our online application and attach your resume.\nAIIS Adatkezelési tájékoztató\nPrivacy notice","description_format":"text","description_chars":2958,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"Advanced (C1)","optional":false}]},"benefits":["Continuous learning","Flexible schedule"],"hiring_locations":[{"name":"Hungary","iso":"HU","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-24T18:40:12Z"}],"liveness":{"score":33,"band":"fade","label":"Fading","p_open":1,"p_active":0.593,"p_room":0.55,"age_days":18,"expected_fill_days":18,"reasons":["conf:4","win:tail","comp:brand"],"computed_at":"2026-09-24T22:55:09Z"},"pay":null,"html_url":"https://alion.io/job/hofer-data-engineer-databricks-pyspark-sql","json_url":"https://alion.io/job/hofer-data-engineer-databricks-pyspark-sql.json","meta":{"generated_at":"2026-09-24T22:55:09Z","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":1147,"day_limit":5000,"remaining_today":3853,"minute_limit":60,"resets_at":"2026-09-25T00:00:00Z"}}}