Data Analyst

• This professional will be responsible for turning data from the Data Lake into actionable insights, supporting strategic and operational decision-making.
• Will work directly on identifying patterns, trends and opportunities, with close collaboration with engineering and AI teams.
• Expected to take an analytical, investigative approach focused on generating business value, especially in a dynamic environment with potential for internal placement at the client.
• Perform advanced exploratory data analyses on large volumes of data
• Identify patterns, anomalies and opportunities in operational and strategic data
• Define, monitor and evolve KPIs and business metrics
• Build reliable metrics ensuring data consistency
• Develop executive and operational dashboards to support decision-making
• Translate complex data into clear insights for business teams
• Collaborate with engineering and data science teams on structuring pipelines
• Explore data in Data Lake environments using AWS tools
• Apply AI-assisted analysis techniques and Large Language Models (LLMs)
• Ensure best practices in visualization, data quality and data governance
• Support decision-making based on structured, hypothesis-driven analyses

Senior Data Analyst

Data Scientist

• Develop and lead machine learning and generative AI solutions
• Design and implement applications using LLMs and agent-based architectures
• Translate business problems into scalable analytical and AI solutions
• Build and validate statistical and machine learning models
• Apply advanced feature engineering techniques
• Develop data pipelines in partnership with engineering
• Implement RAG strategies and tool orchestration
• Evaluate, monitor, and optimize model and LLM performance
• Ensure quality, reliability, and continuous improvement of solutions
• Work with multiple models, balancing cost and performance
• Collaborate with engineering, data, and product teams
• Communicate results and insights clearly to stakeholders.

Senior Data Scientist

Data Engineer

• Develop and maintain scalable data pipelines (batch and streaming)
• Ensure efficient ingestion, transformation, and provisioning of data
• Model data to support analytics and AI applications
• Integrate multiple data sources (APIs, event streams, and internal systems)
• Build and optimize jobs using Spark / PySpark
• Orchestrate pipelines using Step Functions
• Work with event-driven architecture
• Organize and structure data in Data Lake / Lakehouse environments
• Implement data partitioning and optimization strategies
• Ensure pipeline quality, reliability, and observability
• Optimize cost and performance in AWS environments
• Collaborate with data teams (analysts and data scientists) to deliver solutions
• Support technical decisions related to data architecture and engineering

B2

Senior Data Analyst

Senior Data Scientist

Senior/Mid-level Data Engineer