{"id":550722,"url":"https://alion.io/job/navarino-senior-data-engineer-data-quality","title":"Senior Data Engineer - Data Quality","company":{"id":450416,"name":"Navarino","domain":"navarino.co.uk","url":"https://alion.io/company/navarino-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"D","score":50,"open_postings":23,"ghost_share":0.826,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Piraeus, Greece"],"countries":["GR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":77000,"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":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Dagster","optional":true},{"name":"GitHub Actions","optional":true},{"name":"GitLab CI","optional":true},{"name":"Great Expectations","optional":true},{"name":"Jenkins","optional":true},{"name":"Pinecone","optional":true},{"name":"Qdrant","optional":true},{"name":"RAG","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-09-01T00:00:00Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-11-03T14:59:54Z","board_verified":true,"closed_at":null,"days_open":63,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":63},"description":"About us\nNavarino is an innovative global technology company with offices in Greece, Norway, Germany, Cyprus, the United Kingdom, Hong Kong, USA, UAE, Japan and Singapore. We develop technology solutions for the shipping industry and are a leader in our sector. Our R&D and engineering departments focus on building and enriching our product portfolio, with specialized software and services that we develop in-house.\nWe pride ourselves on our people and culture. We encourage innovative thinking, teamwork, and excellence. Our committed people, our values and ways of working create a dynamic, professional, fun, and family-oriented environment which delivers high value and excellence to our customers.\nWhat will you be doing?\nWe are looking for a hands-on Senior Data Engineer with strong expertise in Data Quality to help shape and scale our modern data ecosystem and enable data-driven, AI-centric applications across the organization.\nAs a member of the broader AI team at Navarino, this role will work closely with engineering and business stakeholders to design and build trusted, scalable, and well-governed data platforms that support analytics, operational reporting, machine learning, and next-generation AI solutions.\nThe ideal candidate brings strong data engineering expertise, a passion for data quality and governance, and a commitment to driving best practices across the entire data lifecycle.\nResponsibilities\nDesign, develop, and optimize scalable data pipelines and ETL/ELT processes. \nDefine and implement enterprise-wide data quality principles, frameworks, and standards. \nEnsure data pipelines deliver reliable, accurate, and high-quality data across platforms and business domains. \nDesign and implement strategies that make data Findable, Accessible, Interoperable, and Reusable (FAIR). \nBuild and maintain scalable datasets and data models that support analytics and AI/ML initiatives. \nCollaborate closely with AI, Data Science, Analytics, and Engineering teams to support AI-related projects and production workloads. \nEnsure data assets are cataloged, and metadata (business and technical) is properly maintained to improve discoverability and trust. \nWork with engineers, analysts, and business stakeholders to define data quality requirements for dashboards, models, and operational processes. \nDrive best practices across data architecture, governance, testing, monitoring, documentation, and CI/CD processes. \nSupport cloud-native and multi-cloud data solutions across different cloud providers. \nImprove observability, reliability, security, and operational excellence across the data platform. \nRequirements\nBachelor’s degree in Computer Science, Data Management, Information Systems, or a related field. \nStrong hands-on experience in Data Engineering or Data Quality roles. \nProven experience designing and managing modern data pipelines and large-scale datasets. \nStrong SQL skills and proficiency in programming languages such as Python, Spark, or Scala. \nExperience with pipeline orchestration and modern data tooling. \nExposure to cloud platforms such as AWS, Azure, and/or Google Cloud Platform. \nExcellent communication and stakeholder management skills. \nStrong focus on operational excellence, automation, scalability, and continuous improvement. \nNice to have:\nExperience collaborating with AI/ML or Data Science teams and supporting AI-driven initiatives. \nTrack record implementing and managing data quality frameworks (e.g., Great Expectations, Soda, or Deequ) within modern data platforms. \nExperience with DataOps and/or MLOps practices, including CI/CD for data using tools like GitHub Actions, GitLab CI, or Jenkins.\nExposure to streaming or real-time data architectures using Apache Kafka, Confluent, or Amazon Kinesis. \nExperience working in multi-cloud or hybrid-cloud environments (AWS, Azure, GCP). \nExperience with modern orchestration engines like Apache Airflow or Dagster\nFamiliarity with Vector Databases (e.g., Pinecone, Qdrant, or Weaviate) to support Retrieval-Augmented Generation (RAG) and AI initiatives. \nStrong understanding of data governance, metadata management, and data lifecycle best practices. \nBenefits\nBeyond offering a working environment that values and supports people and their well-being, we at Navarino offer:\nAn attractive financial package \nA generous yearly bonus based on overall company performance and your contributions to the team’s success \nExcellent working conditions with a strong work-life balance \nA wide variety of benefits, including private health insurance \nPersonal development and training opportunities to support your professional growth and continuous learning \nA working environment certified as a \"Great Place to Work\" for five consecutive years (2022-2026), a \"Best Place to Work- Tech\" for 2025 and \"Best Place to Work- Hellas\" 2026","description_format":"text","description_chars":4848,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Health insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Sea Freight","IoT Connectivity"],"lifecycle":[{"event":"open","at":"2026-09-08T14:58:16Z"}],"visa":[],"liveness":{"score":10,"band":"cold","label":"Long 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