{"id":3414201,"url":"https://alion.io/job/sigma-software-group-data-engineer-4","title":"Data Engineer","company":{"id":6266,"name":"Sigma Software Group","domain":"sigma.software","url":"https://alion.io/company/sigma-software-group","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Warsaw, Poland"],"countries":["PL"],"hiring_countries":["PL"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":44000,"max_usd":84000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":19},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EventBridge","optional":false},{"name":"Amazon S3","optional":false},{"name":"API Gateway","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"Great Expectations","optional":false},{"name":"IAM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-28T16:40:40Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-29T16:02:37Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Join a project shaping the future of sustainable energy through cutting-edge data engineering and scientific innovation. We are looking for a Data Engineer to help build scalable cloud-native data platforms for a deep-tech Customer working on one of the most ambitious fusion energy initiatives in the world.\nYou will work with modern distributed data technologies, including Databricks, Apache Spark, AWS, and Azure, while solving complex engineering challenges in a research-intensive environment.\nWe at Sigma Software value engineering excellence, long-term partnerships, and continuous learning. This is an opportunity to contribute to breakthrough scientific initiatives while working with modern technologies and highly skilled global teams.\nPROJECT\nThe project focuses on building and evolving a modern cloud-based data platform supporting scientific research, analytics, and operational workflows in the fusion energy domain. The team develops scalable distributed data processing solutions while ensuring high standards of data quality, lineage, governance, reproducibility, and operational reliability.\nYou will work closely with scientists and engineers to support experimentation, analytics, and machine learning workflows in a highly innovative R&D environment.\n Design, develop, and maintain scalable and reliable data platforms and pipelines for analytics and operational use cases\nBuild distributed data processing workflows using Apache Spark, pySpark, and Databricks\nDevelop and evolve cloud-native data solutions leveraging Azure and AWS services\nModel and optimize data structures for analytics, reporting, and downstream consumption\nIntegrate data from multiple heterogeneous sources while ensuring data quality, consistency, and traceability\nImplement data quality controls, schema validation, lineage tracking, and monitoring processes\nOptimize performance, scalability, reliability, and cost-efficiency of data pipelines and infrastructure\nCollaborate closely with scientists, analysts, and engineering teams to translate business and research requirements into technical solutions\nContribute to CI/CD processes, infrastructure automation, and engineering best practices\nResearch and introduce new technologies and approaches within the data engineering ecosystem\n3+ years of commercial experience in Data Engineering\n2+ years of hands-on production experience with Databricks\nStrong expertise with Delta Lake, including medallion architecture and table optimization\nAdvanced proficiency in Python, pySpark, and SQL\nDeep practical knowledge of Databricks components including Unity Catalog, Lakeflow Jobs / Workflows, and job optimization\nHands-on experience with AWS services including S3, IAM, KMS, and at least one of AWS Batch, ECR, EventBridge, Lambda, or API Gateway\nExperience designing event-driven and asynchronous data pipelines\nStrong knowledge of Infrastructure as Code and CI/CD practices\nPractical experience with Terraform and Databricks Asset Bundles\nExperience working with Git workflows, pull request reviews, and automated testing\nUnderstanding of secure authentication approaches such as OIDC and service principals\nPractical experience with MLflow, experiment tracking, model registry, and reproducibility practices\nStrong understanding of data quality, lineage, schema contracts, and provenance concepts\nExperience with data quality frameworks such as Great Expectations, Soda, pyDeequ, or Databricks DQX\nExperience monitoring and optimizing data platform reliability and cloud costs\nUpper-Intermediate or higher English level\nWILL BE A PLUS:\nExperience packaging workloads using Docker and running batch workloads in AWS\nFamiliarity with ECR and containerized data processing solutions\nExperience with experiment optimization libraries such as scikit-optimize, BoTorch, Ax, or scipy\nUnderstanding of ML feature engineering and leakage prevention techniques\nExperience working in regulated or high-security environments\nKnowledge of data governance, compliance, and data residency requirements\nExperience disabling or restricting AI-assisted tooling/features in secure environments","description_format":"text","description_chars":4127,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Continuous learning"],"hiring_locations":[{"name":"Poland","iso":"PL","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Outsourcing & Dedicated Teams","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-28T18:49:51Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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