Data Engineer

The applicant will design, develop, and implement analytical solutions to support business decisions, applying statistical and machine learning techniques to large datasets for predictive and prescriptive analysis. They will develop data pipelines and ETL processes, collaborate with cross-functional teams to define data requirements, and build dashboards and reports using BI tools like Power BI and Tableau. Additionally, the candidate will write complex SQL queries, manage data in relational and SQL databases, and create documentation for data processes, models, and tools.

The role requires full stack knowledge, including front-end and back-end components, and the ability to set up new infrastructure. The candidate should understand existing hardware and identify additional needs, run compilers and interpreters, manage new databases, and apply machine learning and AI techniques. Hardware experience is crucial for managing large datasets and developing data pipelines, with familiarity in servers, databases, and cloud platforms like AWS for scalable storage and processing.

This position involves working with large datasets, developing data pipelines, and implementing machine learning models. Hardware experience will be particularly useful for setting up and managing the infrastructure needed to support these tasks, ensuring efficient and reliable data processing

Strong SQL and database management experience

-Experience with data pipelines and ETL processes

-Proficiency in machine learning and statistical modeling

-Experience with BI tools (Power BI, Tableau)

-Full-stack development knowledge

-Experience with cloud platforms (AWS preferred)

-Strong understanding of:

-Data architecture

-Data modeling

-Infrastructure setup

-Ability to work with large-scale datasets

-Programming experience (likely Python/R inferred)

-Strong problem-solving and analytical skills

Preferred Skills:

-Experience with AI/advanced machine learning frameworks

-Familiarity with big data technologies (Spark, Hadoop, etc.)

-Experience setting up new environments/infrastructure from scratch

-Knowledge of hardware/server configuration

-Experience in energy/utilities or highly regulated industries

-DevOps or data engineering tooling experience

Education or Certification Requirement:

• Bachelors degree in Electrical Engineering or Computer Engineering

Call Notes:

• 5+ years of relevant experience in data analytics and/or data engineering
• Strong SQL and database management expertise
• Proven experience building, maintaining, and supporting data pipelines and ETL processes
• Strong Python skills for analytics, automation, and statistical applications
• Experience with machine learning, statistical modeling, and advanced analytics
• AWS/cloud experience, including data analysis and database migration projects
• Strong understanding of data architecture, data modeling, and working with large-scale datasets
• Direct Energy/Utilities industry experience, including utility data, EDI transactions, energy applications, rates, invoicing, and account management

• Type of hire: 1 year contract to start, extensions based on performance, possibility of FTE
• Shift/Schedule: 8-hour workday. 8am-5pm (shift times may vary)
• Rate Details: $75-$85/hour

Major Objectives:

-Design and implement advanced analytical solutions

-Build and optimize data pipelines and ETL frameworks

-Develop machine learning models for predictive and prescriptive analytics

-Establish scalable data infrastructure

-Enable business teams through insights, dashboards, and reporting too