{"id":3393431,"url":"https://alion.io/job/softserve-lead-dbt-engineer","title":"Lead DBT Engineer","company":{"id":57039,"name":"SoftServe","domain":"softserveinc.com","url":"https://alion.io/company/softserve","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Bulgaria"],"countries":["BG"],"hiring_countries":["BG"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":39000,"max_usd":98000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2629},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"CI/CD","optional":false},{"name":"dbt","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-28T11:17:30Z","employer_posted_date":null,"last_verified_at":"2026-10-28T11:17:30Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"About the role\n\nIn this role, you will help transform a data platform that currently relies on Spark and Python, orchestrated with Airflow DAGs and stored in Apache Iceberg, into a more modular target architecture centered on dbt and Lakekeeper.\n\nResponsibilities\n\nSupport the migration of the Agora data platform to a cloud-first architecture\n\nDevelop and maintain data transformation logic using dbt as the central business logic layer\n\nRefactor and consolidate logic currently distributed across Spark, Python, and Airflow into a more standardized dbt-based approach\n\nWork with Apache Iceberg as the core storage layer in both current and target architecture\n\nContribute to the implementation of an open and modular platform built around Lakekeeper\n\nSupport data ingestion workflows across Starburst, Microsoft Fabric, and Snowflake\n\nHelp build and maintain scheduling and orchestration processes using dbt and/or Microsoft Fabric\n\nEnable and improve data quality, lineage, documentation, and CI/CD practices across the platform\n\nCollaborate on the transition of the semantic layer from Dremio to Starburst\n\nSupport semantic modeling for analytics using Iceberg views stored in Lakekeeper\n\nWork closely with cross-functional stakeholders to reduce operational complexity and improve platform maintainability\n\nContribute to the development of a flexible data foundation prepared for future analytics and AI-driven use cases\n\nRequirements\n\nStrong experience in data engineering or analytics engineering\n\nHands-on experience with dbt\n\nSolid knowledge of SQL and SQL-based transformation design\n\nExperience with modern data platform and warehouse/lakehouse concepts\n\nPractical experience with Apache Iceberg\n\nExperience with at least some of the following technologies: Spark, Python, Airflow, Starburst, Microsoft Fabric, Snowflake\n\nUnderstanding of data modeling, semantic layers, and analytics-focused data design\n\nExperience with CI/CD, testing, and data quality practices in data platforms\n\nFamiliarity with lineage and technical documentation standards\n\nAbility to work in an open, modular architecture with separated storage and compute principles\n\nUnderstanding of cloud-first platform migration challenges and best practices\n\nStrong collaboration and communication skills\n\nNice to have\n\nExperience with Lakekeeper\n\nExperience migrating from legacy or fragmented data transformation patterns to dbt-centered architectures\n\nFamiliarity with Dremio and migration to Starburst\n\nExperience with ODBC/JDBC-based BI connectivity\n\nExposure to AI-ready data platform design principles\n\nSoftServe is an equal opportunity employer. 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