Senior Systems Engineer supporting the Space Data Network Backbone Program Management Office within the US Space Force Space Systems Command Spectrum Warfare Division.
Compensation
$170- 220k
Responsibilities
Support a broad range of systems engineering activities across the program lifecycle
Serve as customer-facing technical point of contact and lead for technical discussions
Coordinate cross-functional and multi-organizational efforts
Represent the team in a technical capacity to the government customer and external organizations
Manage integration seams with external stakeholders
Requirements
Master's degree or equivalent years of related experience
Nice to have: Previous DoD, Air Force, or Space Force, or Space Systems Command systems engineering experience
Nice to have: Previous experience supporting PMOs in the acquisition of complex systems and/or capabilities
Lead data strategy, governance, and analytics engagements for infrastructure clients, shaping transformation programs and building high-performing teams.
Own and build the lab data platform end-to-end, integrating instrument data, ELN/LIMS, and warehouse pipelines to support modeling and software services.
Responsibilities
Standardize lab data capture and build ingestion tooling
Design and run data pipelines from instruments to BigQuery and Kernel
Model biology and process with schemas linking designs to measurements
Deliver ML-ready datasets and APIs to modeling teams
Build reporting and analysis dashboards for scientists
Concevoir, mettre en œuvre et promouvoir des produits et services digitaux pour des clients grands comptes, en agissant comme interface entre les enjeux business et les équipes d'ingénierie.
Locations (2)
Levallois-Perret, Île-de-France, France
Île-de-France, France
Responsibilities
Recueillir, challenger et formaliser les besoins métiers
Animer des ateliers de cadrage, co-construction et priorisation
Gérer, structurer et faire évoluer le backlog produit
Prioriser les sujets en fonction de la valeur métier, complexité technique, dépendances, risques et enjeux de delivery
Rédiger les user stories, critères d'acceptance et spécifications fonctionnelles
Lead technical resources for the Risk & Reporting team, building data engineering, automation, and dashboards for enterprise reporting workflows in alternative investment strategies.
Locations (2)
Hyderabad
Los Angeles, California, United States
Responsibilities
Design and maintain cloud-ready data pipelines and dimensional models using SQL, Python, Power BI, Microsoft Fabric / Azure, and AWS services such as S3, Glue, Lambda, Redshift, Snowflake or Aurora
Implement secure, automated ingestion from Oaktree systems, MDM, data warehouse sources, FTP / email feeds, vendor files, Salesforce, servicer or administrator reports, and governed reporting datasets
Build performant ELT / ETL workflows for investment, portfolio, cash activity, audit log, exception, exposure, attribution, and reporting-control data
Develop reusable SQL and Python utilities, including advanced SQL optimization, window functions, pandas / PySpark data engineering, REST / GraphQL integration, validation checks, and test automation
Lead enterprise data strategy and architecture across Arxada’s global operations, enabling AI, analytics, and secure data governance.
Locations (2)
Delft, Netherlands, Netherlands
Barcelona, Spain, Spain
Responsibilities
Define and deliver enterprise data strategy and architecture roadmap
Design, govern, and improve enterprise data models and standards
Architect modern data platforms and solutions for data collection, integration, storage, processing, and analytics
Lead design of robust data integration frameworks including APIs, ETL/ELT pipelines, and streaming solutions
Partner with stakeholders to ensure seamless data usability and governance
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics/Statistics, or a related technical discipline
Nice to have: Azure Data Engineer Associate certification
Create institutional Power BI dashboards, semantic models, paginated reports, DAX measures, Power Query / M transformations, row-level security, and deployment pipeline assets
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Data Analytics, Engineering, Statistics, Mathematics, Finance, Accounting or a related analytical field, or equivalent deep work experience building data / BI solutions in investment management
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