Data Analytics Engineer: Pipelines, BI & Quality

Guidehouse; Atlanta (GA); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Medical Insurance

401(k) Plan

Parental Leave

Tuition Reimbursement

Employee Assistance Program

Job summary

Guidehouse in Atlanta is seeking a data analytics, reporting, and data engineering professional to support enterprise data lakes, warehouses, and BI platforms.

You will design and maintain ETL/ELT pipelines using Databricks, ODI, SQL, and Python; build BI semantic layers and dashboards with Power BI, OAS, and Tableau; ensure data quality and governance; collaborate with stakeholders to deliver scalable data solutions.

Qualifications

• Bachelor's degree in a technical field.
• Three (3) or more years of professional experience supporting data analytics, reporting, data engineering, or BI initiatives.
• Hands-on experience supporting enterprise data lakes, data warehouses, and analytics platforms.
• Strong expertise with Databricks, ODI, SQL, Python, and ETL/ELT development.

Responsibilities

• Support data analytics, reporting, and data engineering across data lakes, warehouses, and BI platforms.
• Design, develop, and maintain ETL/ELT data pipelines.
• Utilize Databricks, ODI, SQL, and Python to transform large datasets.
• Perform data quality assessments and metadata documentation for governance.
• Develop BI semantic layers and scalable reporting solutions.

Skills

Databricks

ETL/ELT

SQL

Python

Data governance

Data quality

Metadata management

BI semantic layer

Dashboarding

Data integration

Education

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related technical field.

Tools

ODI

Power BI

Tableau

Oracle Analytics Server

Databricks

Job description

Guidehouse in Atlanta is seeking a data analytics, reporting, and data engineering professional to support enterprise data lakes, warehouses, and BI platforms.

You will design and maintain ETL/ELT pipelines using Databricks, ODI, SQL, and Python; build BI semantic layers and dashboards with Power BI, OAS, and Tableau; ensure data quality and governance; collaborate with stakeholders to deliver scalable data solutions.