Quick overview
Job description
Data Engineer
Position Overview
We are seeking a hands-on Data Engineer to help build and evolve a modern, centralized data platform. This role will work with large volumes of data coming from a variety of internal and external sources, transforming raw and sometimes inconsistent information into clean, structured, reliable datasets that can be used across the business.
The ideal candidate is a strong data engineer at their core: someone who has personally built ETL/data pipelines, understands data transformation and modeling, and is comfortable working independently with complex datasets. This is not a reporting-focused or Data Analyst position.
Responsibilities
- Design, build, and maintain scalable end-to-end ETL/data pipelines
- Ingest data from a variety of internal and external sources
- Clean, transform, validate, and structure large volumes of raw data
- Work with multiple data formats, including Excel, CSV, JSON, ORC, and Parquet
- Load and organize transformed data within database and data lake environments
- Design scalable data models based on business and analytical requirements
- Build the underlying data and semantic layers used for reporting and analytics
- Help develop and expand a centralized enterprise data platform
- Work with datasets that can reach billions of rows
- Prepare trusted, well-structured data for downstream use across Power BI, advanced analytics, and future AI applications
- Partner with business and technical stakeholders to understand how data needs to be structured and consumed
Required Qualifications
- Strong hands-on data engineering and ETL experience
- Demonstrated experience personally designing and building production data pipelines
- Strong SQL skills
- Strong experience with data transformation and data modeling
- Experience working with large, complex datasets from multiple sources
- Ability to take messy or unstructured source data and turn it into clean, usable datasets
- Experience working with data lakes, databases, and modern data architectures
- Ability to translate business data requirements into scalable technical solutions
- Comfortable working independently and owning projects from requirements through implementation
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