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Hire the best data experts, fast 

Interim & project-based staffing

Talk to a staffing specialist

What you can hire us for

1

Staff augmentation (1-2 profiles) 

Need extra hands fast?

We provide 1–2 experienced data professionals who plug straight into your team — analysts, BI developers, data engineers, or governance specialists.

Perfect for short-term gaps, project spikes, or temporary expertise.

2

Agile squads (2 - 6 specialists)

For larger initiatives, we build cross-functional teams (2–6 experts) that deliver end-to-end data solutions.

Think analyst + BI dev + data engineer + analytics engineer working together under agile delivery.

Ideal for accelerating BI rollouts, migrations, or governance programs.

3

Interim leadership 

When you need direction without a full-time hire, our fractional data leaders step in.

Interim Head of Data/BI, Data Governance Lead, or Analytics Manager; experienced professionals who guide strategy, structure teams, and ensure delivery continuity.


Domains of expertise 

Data Analysis 

Our team of Data Analysts excels in gathering, organizing, and interpreting statistical data using state-of-the-art analysis tools. 

We process complex datasets to extract meaningful insights that not only reveal underlying patterns but also highlight opportunities and challenges. 

These critical insights enable our clients to make well-informed, strategic business decisions, driving growth and efficiency in their operations.

Skillset: SQL, NO SQL, Data cleaning, Tableau, PowerBI, Excel, Python, ...  

Data Engineering

Our data engineers are experts in preparing and managing large-scale data infrastructures that support comprehensive analytics performed by data analysts and scientists. 

They are responsible for designing robust data systems, building scalable architectures, modeling data, integrating diverse data sources via ETL pipelines, ensuring continuous integration and delivery, as well as ensuring continuous data availability and integrity.  

Skillset: Python, GCP, AWS, Azure, Cloudera, SQL Server, ETL, Spark, Kafka, Data Vault, Kimball, ...

Data Science

Our data scientists analyze and interpret raw data into business solutions using machine learning and algorithms. 

Data science looks at the probability of future events and conditions. Predictive analysis uses historical data to forecast business trends, customer behavior, and product success. 

It seeks to answer questions about what will happen in the future. Prescriptive analysis seeks to find a solution to a specific business problem.

Skillset: Python, R, Machine Learning, SQL, noSQL, NLP, Hadoop, SAS, Spark, ...

Data Management

Our services offer comprehensive data management and governance, ensuring your organization's data is not only a valuable resource but also meticulously managed and governed. 

We focus on enhancing data quality, ensuring compliance, and creating a unified architecture to facilitate efficient data utilization and strategic analysis. 

This approach supports superior decision-making and operational efficiency across all levels of your organization.

Skillset: Data Governance, Data Quality, Master Data Management, Data Architecture, ...

Which roles can we support?

Data Analysis

Data analysts deliver value to their companies by taking data, using it to answer questions, and communicating the results to help make business decisions. 

Common tasks done by data analysts include data cleaning, performing analysis and creating data visualizations.

Skills: Excel, SQL, PowerBI, Tableau, Python, ...


The nature of the skills required will depend on the company’s specific needs, but these are some common tasks:

  • Cleaning and organizing raw data.
  • Using descriptive statistics to get a big-picture view of their data.
  • Analyzing interesting trends found in the data.
  • Creating visualizations and dashboards to help the company interpret and make decisions with the data.
  • Presenting the results of a technical analysis to business clients or internal teams.

Data Engineering

Data engineers build and optimize the systems that allow data scientists and analysts to perform their work. Every company depends on its data to be accurate and accessible to individuals who need to work with it. 

The data engineer ensures that any data is properly received, transformed, stored, and made accessible to other users.

Skills: Statistical machine learning & algorithms, stochastic processing, natural language processing,…

The data engineer’s mindset is often more focused on building and optimization. The following are examples of tasks that a data engineer might be working on:

  • Building APIs for data consumption.
  • Integrating external or new datasets into existing data pipelines.
  • Applying feature transformations for machine learning models on new data.
  • Continuously monitoring and testing the system to ensure optimized performance

Data Science

A data scientist is a specialist who applies their expertise in statistics and building machine learning models to make predictions and answer key business questions.

Skills: Statistical machine learning & algorithms, stochastic processing, natural language processing, …

A data scientist still needs to be able to clean, analyze, and visualize data, just like a data analyst. However, a data scientist will have more depth and expertise in these skills and will also be able to train and optimize machine learning models:

  • Evaluating statistical models to determine the validity of analyses.
  • Using descriptive statistics to get a big-picture view of their data.
  • Testing and continuously improving the accuracy of machine learning models.

Business Intelligence

Our business intelligence experts use descriptive analysis to present historical data to business units in a way that makes it easy for them to visualize and understand. 

Business Intelligence is often used to generate reports that clearly and accurately communicate the current state of the business.

Skills: PowerBI, Tableau, SQL, Qlikview, programming skills, ...

They are responsible to build the data warehouse applications to support business intelligence requirements of a company. There are several niche roles within the umbrella of data warehousing engineers:

  • Data Architects to design the architecture for the data warehouse. They work along with other enterprise architects.
  • Data modellers to design the data model for the data warehouse, such that it is optimised for querying data.
  • Source system analysts to create data mappings from source system to data warehouse.
  • ETL developers to build ETL interfaces to load data into the data warehouse.
  • Business Intelligence developers to build reports and visualizations for business users.

Our process (days, not months)

1

In-take (0-1 day)

Goals, stack, must-haves.

2

Shortlist ( ≤ 72h)

2–4 screened candidates with rates & availability.  

3

Interviews (1-5 days)

We coordinate and collect feedback.

4

Start

Contracts & onboarding support.  

5

Follow-up

Weekly check-ins; fast replacement if needed.  

Why Dark Light?

We do staffing a little differently. Our approach is built on speed, transparency, and fairness; values that keep both clients and consultants coming back.

Transparent rates

You always know what you pay and what goes to the consultant.

Competitive margins

Service tailored to our client & expert, guaranteed win-win-win.

Fast delivery

Receive a curated shortlist within 72 hours.

Data-only focus

We specialize in BI, analytics, and data roles — nothing else.

Let's work together
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Which roles can we support?


person in blue shirt writing on white paper

Data Analyst

Data analysts turn raw data into insights that drive business decisions. 

They clean and organize data, analyze trends, and build dashboards or reports to communicate findings clearly.

Core skills: Excel, SQL, Python, Power BI, Tableau 

black flat screen computer monitor

Data Engineer

Data engineers design and maintain the systems that make data reliable, accessible, and usable for analysis. 

They build pipelines, integrate data sources, and optimize infrastructure to support data-driven work.

Core skills: Data pipelines, APIs, machine learning workflows, NLP, optimization 

blue and white floral textile

Data Scientists

Data scientists use statistics and machine learning to uncover insights and make predictions that guide strategic decisions.

They go beyond analysis to build, test, and refine predictive models.

Core skills: Machine learning, statistics, NLP, model evaluation 

turned on monitoring screen

Business Intelligence & DWH experts

Our BI experts transform historical data into clear, visual insights that help teams understand and act on the current state of the business. They design and build data warehouses, dashboards, and reports tailored to decision-makers.

Core skills: Power BI, Tableau, SQL, QlikView, ETL, data modeling 

Get in touch

Let's connect.

Email

       connect@dark-light.be

Phone

        +32 3 303 44 09 

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