Data Engineer

Vaco is partnered with a fast growing client to bring in a Senior Data Engineer who is highly collaborative and self‑starting. In this role, you will play a pivotal role in a critical, high‑visibility initiative to optimize our client’s process around new store location selection and how they open new locations. We are looking for those with strong data integration and engineering skills, who will build a scalable, data‑driven foundation to fuel future growth.

You will be a core member of a cross‑functional project team, working alongside representatives from Real Estate, Legal, and the Site Selection team. Your primary mission will be to solve challenges related to fragmented data sources, build robust data pipelines, and create a centralized, trustworthy Snowflake data lake that supports advanced analytics and AI/ML models across the enterprise. This is a unique opportunity to see your work directly impact major business decisions, reduce financial risk, and accelerate speed to market.

We are looking to move quickly on this position, so please reach out to the Vaco team today to learn more… this will not last long! Core Responsibilities Design, build, and maintain scalable and reliable data pipelines using our modern data stack (AWS, Snowflake, DBT, Workato). Be responsible for the complete data lifecycle, including ingestion, normalization, and stewardship of key Real Estate and Legal contract data.

Collaborate closely with data scientists to provide clean, reliable features for machine learning models, helping to improve new store forecast accuracy. Operationalize data ingestion from various source systems, including Procore, LawVu, and Lucernix, to support the automation of the new store pipeline. Own the development of a master data source for Real Estate in the company’s data lake (Snowflake), which will serve as the system of record.

Partner with stakeholders to map out critical processes and identify high‑ROI automation opportunities. Help transition the team from manual, labor‑intensive analysis to a future state of scalable, automated model generation and trustworthy data pipelines. Position Qualifications Proven experience as a Data Engineer in a cloud‑based environment, preferably AWS.

Hands‑on experience with a modern data stack, including a cloud data warehouse (Snowflake), data transformation tools (DBT), and integration platforms (Workato or similar). Strong experience with bulk data loads (Boomi, Mulesoft, Tibco, Informatica). Strong proficiency in SQL and experience building and maintaining robust data pipelines.

Demonstrated ability to work with fragmented data from multiple systems to create a single, trusted source of truth. Integration experience with low‑code IPAAS like Workato. Excellent communication skills and experience working in a collaborative, cross‑functional team.

A self‑starter mentality with the ability to drive projects forward and solve complex problems in a dynamic environment. (Preferred) Experience supporting MLOps or Data Science teams, particularly with feature engineering and scoring. (Preferred) Familiarity with data related to Real Estate, legal contracts, or multi‑site retail operations. Bachelor’s degree in Computer Science, Engineering, or a related technical field. Areas of Influence High Impact: Your work will directly contribute to a foundational capability for the enterprise and influence multi‑million dollar real estate decisions.

Modern Tech: You will work with a cutting‑edge, cloud‑native data stack and help shape our AI and MLOps patterns. Collaborative Culture: You will be a key, dedicated resource on a project team focused on innovation and solving challenging problems. Growth: This role offers the chance to build new systems from the ground up and establish the data engineering best practices that will allow us to scale effectively. #J-18808-Ljbffr