Data Engineer 3 4P/444

4P Consulting Inc.; Atlanta, Birmingham (GA, AL); Hybrid; USD 90,000 - 120,000; Full time

Job summary

A consulting firm is seeking an experienced Data Engineer III to build and maintain scalable data pipelines. The role requires proficiency in Databricks, Azure, and strong skills in SQL optimization and data transformation. The ideal candidate will have 5-10 years of relevant experience and expertise in data modeling and pipeline development. This position operates within the business technology/data domain and focuses on ensuring clean and accessible data assets.

Qualifications

• 5-10 years in a Data Engineering role with hands-on development.
• Strong background in data manipulation and software engineering-oriented data practices.
• Experience supporting enterprise-scale platforms.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Implement transformations using Spark, SQL, and ETL/ELT tools.
• Ensure data consistency, accuracy, completeness, and reusability.

Skills

Data transformation

SQL optimization

Databricks

Azure

Spark

Hive

Airflow

Tools

Databricks

Azure

Spark

Hive

Airflow

Job description

Data Engineer III

Experience: 5–10 Years
Location: Birmingham, AL/ Atlanta, GA
Contract- 1 Year

Client- Alabama Power

Position Overview

We are seeking an experienced Data Engineer (Level 3) to build, optimize, and maintain scalable data pipelines and datasets that support business-critical analytics and applications. This role sits outside traditional IT and operates within the business technology/data domain—focused on ensuring clean, structured, and accessible data assets.

The ideal candidate will have deep experience in data transformation, SQL optimization, Data Lakehouse architectures, and distributed processing systems. Proficiency in Databricks, Azure, Spark, Hive, and Airflow is required.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain scalable and reliable data pipelines

• Combine raw data from multiple sources into clean, structured, machine-readable datasets

• Implement transformations using Spark, SQL, and ETL/ELT tools

• Normalize and model relational and distributed datasets to support analytics & applications

Lakehouse & Cloud Engineering

• Develop and optimize data architectures in Databricks Lakehouse & Azure

• Manage ingestion pipelines across structured and unstructured data sources

• Apply data governance, quality, and lineage methodologies in cloud environments

Data Modeling & Quality

• Create logical and physical data models to support business intelligence, ML, and analytics workloads

• Ensure data consistency, accuracy, completeness, and reusability

• Establish data quality frameworks, validation checks, and monitoring automation

Experience

• 5–10 years in a Data Engineering role with hands‑on development

• Strong background in data manipulation & software engineering-oriented data practices

• Experience supporting enterprise-scale platforms

Technical Skills

• Advanced SQL (query optimization, stored procedures, tuning)

• Databricks & Microsoft Azure Cloud (mandatory)

• Spark / Hive / Airflow

• Strong data modeling (star, snowflake, third-normal form)

• Experience building ETL/ELT pipelines in distributed environments