Position Overview

As a Consultant in our Professional Services team, you will act as a trusted technical advisor to our clients, helping them unlock the value of their data. You will bridge the gap between business requirements and technical execution, designing and building robust data pipelines, analytics frameworks, and AI/ML-driven solutions.

This role is ideal for a high-performing Data Engineer or Analytics Consultant who thrives in a client-facing environment, loves solving complex data puzzles, and wants to deliver cutting-edge data and AI solutions.

Key Responsibilities

• Delivery & Implementation: Partner with clients to implement scalable data engineering pipelines, data models, data warehouses, and analytics platforms from inception to deployment.
• Data Infrastructure & Platform Management Set up and configure the underlying platforms — storage, compute clusters, data warehouses. Identify and implement performance tuning as required.
• Analytics & Insights: Develop advanced analytics models, dashboards, and reporting frameworks that provide actionable business intelligence to client stakeholders.
• AI/ML Integration: Assist clients in integrating AI/ML capabilities, LLMs, and predictive analytics into their existing data ecosystems and business workflows.
• Best Practices: Ensure high data quality, governance, security, and performance optimization across all client deliverables.

Required Skills & Qualifications

• Experience: 2–5 years of experience in Data Engineering, Data Analytics, or a data-focused technical consulting role.
• Cloud Data Ecosystems: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and core modern data stack tools (e.g., Snowflake, Databricks, BigQuery, dbt).
• Data Engineering: Strong proficiency in Python or Scala, and advanced SQL. Experience building batch and real-time data pipelines.
• Analytics & AI: Experience working with data science libraries (e.g., Pandas, NumPy, Scikit-Learn, pytorch) and a solid understanding of deploying AI/ML models or integrating AI APIs.
• Data Modeling: Solid understanding of data warehousing concepts, data modeling (Star/Snowflake schema), and data architecture principles.
• Consulting & Communication: Excellent client-facing communication skills, with the ability to manage stakeholder expectations, write clear documentation, and present complex technical concepts simply.

Preferred Qualifications

• Higher education degree in Engineering, Computer Science, IT/Data science, or equivalent field experience.
• Experience with BI and data visualization tools (e.g., Tableau, PowerBI, Looker).
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines for data (MLOps/DataOps).
• Prior experience working in a Professional Services, Professional Consulting, or IT Advisory capacity.
• Familiarity with RAG.
• English speaking required, Spanish speaking is a plus.