Data Analyst/Engineer

at  Spektrum

Spektrum have a wide range of exciting opportunities in several global locations.
We are always looking to add great new talent to our team and look forward to hearing from you.
Spektrum supports apex purchasers (NATO, UN, EU, and National Government and Defence) and their Tier 1 supplier ecosystem with a wide range of specialist services. We provide our clients with professional services, specialised aerospace and defence sales, delivery, and operational subject matter expertise. We are looking for personnel to join our team and support key client projects.

WHO WE ARE SUPPORTING

Allied Command Transformation (ACT) is NATO’s leading agent for change: driving, facilitating, and advocating the continuous improvement of Alliance capabilities to maintain and enhance the military relevance and effectiveness of the Alliance. The main objectives of ACT are: providing appropriate support to NATO missions and operations; leading NATO military transformation; improving relationships, interaction, and practical cooperation with partners, nations, and international organisations. ACT therefore leads Alliance concept development, capability development, training, and lessons-learned initiatives and provides unfettered military support to policy development within NATO.

EDUCATION

• A University Degree in a relevant engineering, management, information systems, accounting, economics, finance, business administration, public administration, operations research, project management, or related discipline. Professional experience in data analytics/engineering of min. 5 years will be accepted instead of a degree in a relevant field.

Essential Qualifications

• This role is a hybrid of data analysis and data engineering and will require you to have skills in both areas.
• Demonstrable recent experience (at least 5 years in the last 10) in complex data analysis and processing. List the most relevant projects supported, analytical artifacts produced, or data engineering tasks performed.
• Demonstrable recent hands-on experience (at least 3 years in the last 10) in using modern software architecture and software development related to data science, analytics, and data integration, e.g. Python, SQL, KNIME, Pentaho or similar, and familiarity with working with semi-structured data (XML, JSON) and APIs. List the most relevant projects supported (no more than 3), tools/languages used, and nature of the source data (e.g. relational, free text, JSON/XML).
• Demonstrable recent hands-on experience (at least 3 years in the last 10) in designing and implementing data warehouse and data lake solutions. Knowledge of different data modeling paradigms, e.g. relational, dimensional, triple store (semantic Wikis), NoSQL. List the most relevant projects supported (no more than 3), tools used, and data modeling paradigm used.
• Effective storytelling via data, Experienced ‘data storyteller’. Provide the most relevant examples (no more than 3) together with the type of audience, ‘data story’ presented, and presentation goals and outcomes.
• Demonstrable recent hands-on experience (at least 2 years in the last 5) with data presentation and visualization tools, e.g. Microsoft Power BI, Tableau, Kibana, or similar using high-quality graphs and reports, charts, heat maps, and interactive dashboards. List the most relevant projects supported (no more than 3), types of visualizations, and tools used

• Gather and analyze data related to enterprise architecture and capability architectures: This includes data on capabilities, processes, data flows, requirements, and program portfolio.
• Create architectural dashboards and heat maps. Use data to visualize the architecture maturity, architectural links and gaps between initiatives, requirements fulfillment, the status of programs and projects, and identify potential risks and bottlenecks.
• Use data to create architectural roadmaps for capability development, and identify the capabilities to support future initiatives and NATO Digital Transformation.
• Collaborate with enterprise architects and capability architects to develop and implement data-driven architecture strategies. Work closely with the architects to understand their needs and deliver actionable insights.
• Integrate data sources relevant to the enterprise architecture (capability architectures, taxonomies, requirements, and program/project information).
• Develop, construct, test, and maintain data pipelines and data processing tools such as databases, data warehouses, and ETLs.
• Transform data into formats that can be easily analyzed by developing, maintaining, and testing infrastructures for data generation.
• Configure, integrate, and maintain data integration and analytics tools and shared repositories (e.g. PowerBI, KNIME, SQL Server and other DBMS’, SharePoint).
• Improve data quality and efficiency.
• Support evaluation of capability requirements and objectives and their delivery status.

• Perform additional tasks as required by the COTR related to the labor category.

  Essential Qualifications

• This role is a hybrid of data analysis and data engineering and will require you to have skills in both areas.

• Demonstrable recent experience (at least 5 years in the last 10) in complex data analysis and processing. List the most relevant projects supported, analytical artifacts produced, or data engineering tasks performed.
• Demonstrable recent hands-on experience (at least 3 years in the last 10) in using modern software architecture and software development related to data science, analytics, and data integration, e.g. Python, SQL, KNIME, Pentaho or similar, and familiarity with working with semi-structured data (XML, JSON) and APIs. List the most relevant projects supported (no more than 3), tools/languages used, and nature of the source data (e.g. relational, free text, JSON/XML).
• Demonstrable recent hands-on experience (at least 3 years in the last 10) in designing and implementing data warehouse and data lake solutions. Knowledge of different data modeling paradigms, e.g. relational, dimensional, triple store (semantic Wikis), NoSQL. List the most relevant projects supported (no more than 3), tools used, and data modeling paradigm used.
• Effective storytelling via data, Experienced ‘data storyteller’. Provide the most relevant examples (no more than 3) together with the type of audience, ‘data story’ presented, and presentation goals and outcomes.
• Demonstrable recent hands-on experience (at least 2 years in the last 5) with data presentation and visualization tools, e.g. Microsoft Power BI, Tableau, Kibana, or similar using high-quality graphs and reports, charts, heat maps, and interactive dashboards. List the most relevant projects supported (no more than 3), types of visualizations, and tools used.