{"id":4269546,"url":"https://alion.io/job/globaldev-group-senior-data-engineer","title":"Senior Data Engineer","company":{"id":173118,"name":"Globaldev Group","domain":"globaldev.tech","url":"https://alion.io/company/globaldev","size_band":"201-500","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":92,"open_postings":3,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":32,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":{"label":"CET","utc_offset_min":1,"utc_offset_max":1},"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["PL","UA"],"hiring_countries_total":2,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon S3","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-13T17:23:09Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T17:23:09Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"M Science is a data-driven research and analytics firm, uncovering new insights for leading financial institutions and corporations. We come to work every day to create actionable insights from alternative data. M Science is revolutionizing research, discovering new data sets and pioneering methodologies to provide actionable intelligence. Our research teams have decades of experience working with massive amounts of unstructured data in near real-time to discern critical insights that help clients make smarter, more informed decisions. We combine the best of finance, data and technology to create a truly unique value proposition for both financial services firms and major corporations.\nWe're looking for a Senior Data Engineer who is passionate about building robust, scalable data infrastructure and pipelines. You'll work with petabytes of data daily using cutting-edge technologies including Databricks, SQL, Python, Airflow, and modern AI development tools. This role requires someone who can architect solutions, mentor junior engineers, and drive technical excellence across our data platform.\nNOTE: This role requires flexible working hours to ensure at least 2 hours of overlap with colleagues based on both the US East Coast and West Coast. Expected working schedule: 12:00-20:00 CET.\nResponsibilities:\nDesign, build, and maintain scalable ETL/ELT pipelines processing petabytes of data;\nArchitect data solutions using modern cloud technologies (AWS, Databricks, Snowflake);\nImplement real-time and batch processing workflows using Apache Airflow;\nOptimize data storage and retrieval patterns for analytical workloads;\nImplement comprehensive data quality frameworks and monitoring systems;\nEstablish data governance standards and best practices;\nBuild automated testing and validation for data pipelines;\nDevelop data lineage and metadata management solutions;\nLead technical design reviews and architecture decisions;\nMentor junior data engineers and promote best practices;\nDrive adoption of modern development practices including CI/CD for data pipelines;\nLeverage AI coding assistants (Cursor, Claude, GitHub Copilot) to accelerate development;\nImplement AI-driven data quality checks and anomaly detection;\nStay current with emerging AI tools and their applications in data engineering.\nRequirements:\n3-8 years of data engineering experience;\nExpert-level SQL - Complex queries, performance optimization, window functions;\nAdvanced Python - Object-oriented programming, async/await, data processing libraries;\nApache Airflow - DAG development, custom operators, workflow orchestration;\nDatabricks - Spark optimization, Delta Lake, Unity Catalog governance;\nCloud Platforms - AWS (S3, EMR, Lambda, Glue) or equivalent;\nData Modeling - Dimensional modeling, data vault, modern data stack patterns;\nExperience mentoring junior engineers and leading technical initiatives;\nStrong communication skills for cross-functional collaboration;\nExperience with Agile methodologies and project management;\nAbility to translate business requirements into technical solutions.\nWill be a plus:\nExperience in financial services, fintech, or data intelligence companies;\nBackground in consumer retail, digital media, or technology verticals;\nAdvanced degree in Computer Science, Statistics, Mathematics, or related field.\nWhat we offer:\n20 days of vacation;\nPublic holidays;\nMobilization reservation available upon successful completion of the probation period (for Ukrainian colleagues);\nThe exchange of experience and work with talented colleagues;\nLast but not least - 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