{"id":4027594,"url":"https://alion.io/job/softserve-senior-data-engineer-apache-kafka","title":"Senior Data Engineer (Apache Kafka)","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":{"grade":"A","score":100,"open_postings":7,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","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":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Feature Store","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-10T13:59:38Z","employer_posted_date":null,"last_verified_at":"2026-11-10T13:59:38Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"ABOUT THE ROLE\n\nIn this role, you will work as a Senior Data Engineer on a next-generation data platform supporting a broad portfolio of energy-sector products.\n\nYou will design canonical and semantic data models, integrate fragmented data sources, build real-time pipelines, and take ownership of the Apache Kafka platform. The role is focused on creating reliable, reusable data foundations for cross-product reporting, analytics, AI/ML, and data observability.\n\nRESPONSIBILITIES\n\nDesign and maintain canonical and semantic data models across multiple products and data domains\n\nDefine data contracts, standards, and integration patterns for heterogeneous systems\n\nBuild and maintain batch and real-time data pipelines\n\nArchitect, deploy, and administer Apache Kafka clusters\n\nOwn Kafka topic and partition design, replication, security, monitoring, capacity planning, and performance tuning\n\nCreate data foundations for reporting, analytics, machine learning, and LLM-based capabilities\n\nImplement data lineage, usage tracking, telemetry, observability, and data quality monitoring\n\nCollaborate with product managers, data scientists, and application engineering teams\n\nDefine and maintain data dictionaries, integration specifications, and architecture documentation\n\nDrive cross-product data integration in complex and evolving environments\n\nREQUIREMENTS\n\n5+ years of professional data engineering experience\n\nExpert-level hands-on Apache Kafka experience, including production cluster setup and administration\n\nStrong experience with Kafka broker configuration, topics, partitions, replication, SASL/SSL, ACLs, schema registry, monitoring, alerting, and performance tuning\n\nDeep expertise in canonical and semantic data modelling\n\nStrong experience integrating data across heterogeneous systems with different schemas, frequencies, and business contexts\n\nStrong SQL and Python skills for production data engineering\n\nExperience designing data platforms for reporting, analytics, AI, and machine learning use cases\n\nStrong understanding of data contracts, integration standards, and reusable data architectures\n\nExcellent technical documentation and written communication skills\n\nAbility to work autonomously and drive solutions in ambiguous environments\n\nExperience with data observability, lineage, telemetry, and data quality monitoring is strongly preferred\n\nExperience with Databricks, Microsoft Fabric, Snowflake, SageMaker, or similar platforms is an advantage\n\nExperience supporting AI/ML pipelines, feature stores, training datasets, or embedding-ready data structures is an advantage\n\nKnowledge of Kimball, Data Vault, and medallion architecture approaches is preferred\n\nExperience with energy, Oil & Gas, or industrial operational data is a strong advantage\n\nSoftServe is an equal opportunity employer. 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