{"id":4232997,"url":"https://alion.io/job/globaldev-group-data-engineer","title":"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":null,"employment_type":null,"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":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-13T10:50:17Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T10:50:17Z","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 exceptional data engineers who will work with petabytes of data daily using diverse technologies like Databricks, SQL, Python, Airflow, and others. You will be expected to effectively partner with upstream engineering teams and downstream consumers, including analysts and product engineers. In this role, you will build datasets to support analytics, experimentation, and machine learning. Specifically, you will build out standards for pipelining at scale, including establishing common operators, workflows/DAGs, and optimizing existing products.\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:\nManage and improve pipeline for cleansing, filtering, and structuring raw datasets for the purposes of company and customer analysis.\nImplement QA procedures to proactively identify data anomalies and issues.\nImplement new products and features created by analyst teams using best practices.\nWork with other team members and internal stakeholders on infrastructure projects, documentation, QA and code reviews.\nBuild and manage Repos.\nContinuously seek opportunities to standardize code and automate production pipelines.\nCreate and contribute to frameworks that improve the efficacy of logging data, while working with infrastructure to triage issues and resolve.\nMentor team members by giving/receiving actionable feedback.\nRequirements:\n3-7 years of experience as a data engineer.\nPreference given to those that have worked in a similar type role within a data intelligence company or within our desired verticals including consumer retail & brands, digital media and technology.\nExpertise in data engineering in a cloud environment (Python, Databricks, AWS, Airflow, Snowflake, SQL).\nSQL & Python required.\nWorking knowledge of PySpark and distributed computing.\nStrong people and management skills to interact with product managers and data analysts.\nFamiliarity with software development methods such as Scrum and TDD.\nGeneral project management skills.\nAbility to clearly articulate project plans, technical requirements, methodologies, and takeaways to both technical and non-technical stakeholders.\nBachelor’s or higher degree, or significant experience in Statistics, Mathematics, Computer Science, or a similar quantitative discipline.\nAbility to thrive in a culture of quality and personal accountability.\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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