Data Engineer I

Talent Team•Escondido, CA

9d•Onsite

About The Position

At Baker Electric we are energized by truly living our values - Team Builders, Relentless Follow Through, All-In, and Care for Others. When our team members work together with these things in mind, we do great things both individually and as an organization. Being an employee-owned company shows our drive for sustainable, long-term growth while enhancing the lives of our team members. SUMMARY: The Data Engineer I supports the development and maintenance of data pipelines, integrations, and reporting solutions that enable analytics and business intelligence across the organization. This role works closely with senior members of the IT Applications and Data team to build reliable data foundations, learn construction industry data workflows, and grow technical skills in cloud-based data platforms. This position is ideal for an early-career data engineer looking to develop hands-on experience in a collaborative, enterprise environment. This role works on-site 5 days per week in Escondido, CA.

Requirements

Programming: Working knowledge of SQL. Exposure to Python or similar scripting language preferred.
Data Platforms: Familiarity with cloud-based data platforms such as Azure, AWS, or GCP. Exposure to data warehouses or data lakes is a plus.
Tools: Experience with Power BI or similar data visualization tools preferred. Exposure to ETL, ELT, or integration tools is a plus.
Bachelor’s degree in computer science, data engineering, information systems, or a related field, or equivalent practical experience.
1 - 3 years of professional experience in data, analytics, or engineering related role
Internship, academic, or project-based experience is acceptable and may be considered in lieu of direct professional experience.
Strong analytical and problem-solving skills with attention to detail.
Ability to communicate effectively with both technical and non-technical audiences.
Collaborative and team oriented, with strong interpersonal skills and a service mindset.
Foundational understanding of data concepts including data integration, quality, and security best practices.
Organized, self-motivated, and able to manage tasks in a fast paced environment with guidance.
Willingness to research issues, learn new tools and technologies, and continuously improve skills and processes.

Nice To Haves

Background in construction, energy, or industrial services industry.
Experience with enterprise applications such as Procore, BuildOps, Spectrum, Salesforce, or Dayforce.
General understanding of construction project lifecycle concepts, cost codes, or operational data.
Exposure to Building Information Modeling (BIM) and project management software.

Responsibilities

Data Collection and Integration: Assist with extracting data from enterprise systems such as ERP, project management, estimating, HCM, and operational tools. Support integration efforts under the guidance of senior data engineers.
SQL Development and Optimization: Write, optimize, and troubleshoot SQL queries and stored procedures for data extraction, and manipulation.
Data Cleaning and Transformation: Perform data cleansing, validation, and normalization tasks to ensure data accuracy and consistency. Assist in identifying data quality issues and escalating them as appropriate.
Data Pipeline Development: Build and maintain ETL processes with guidance from senior team members. Monitor data pipelines and assist with troubleshooting and issue resolution.
Data Modeling Support: Contribute to data models and schemas designed by senior engineers. Document data definitions, transformations, and dependencies.
Infrastructure: Manage databases, data warehouses, and data lakes, ensuring performance and reliability.
Reporting and Analytics Support: Assist with dashboard and report development using Power BI or similar tools. Validate data accuracy and support enhancements and updates.
Learning and Growth: Participate in technical reviews, documentation efforts, and team discussions. Build knowledge of construction industry data concepts, systems, and workflows.