Data Engineer

Attractivate Consulting Solutions; Atlanta (GA); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Attractivate Consulting Solutions is seeking a Data Analytics / Data Engineer for an Atlanta-based role in the oil and gas sector. The role focuses on building scalable data pipelines and enabling enterprise BI capabilities.

You'll work at the intersection of data engineering and analytics, using Databricks and Microsoft Fabric, with Lakehouse architectures, Power BI integration, and Azure cloud in a hybrid/on-site setting.

Qualifications

• 3+ years of experience in data engineering or analytics-focused roles.
• Strong hands-on experience with Databricks (Spark, Delta Lake, notebooks, jobs, workflows).
• At least 1 year of experience with Microsoft Fabric, including Data Factory and Lakehouse/OneLake.
• Proficiency in SQL and Python.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT with Databricks.
• Develop and optimize data models to support analytics and reporting.
• Leverage Microsoft Fabric (Data Factory, Lakehouse, OneLake) to ingest and transform data.
• Partner with analysts and stakeholders to understand data needs and deliver insights.
• Ensure data quality, governance, security, and performance across platforms.
• Monitor pipeline performance and troubleshoot failures.
• Document data workflows, models, and best practices.

Skills

Databricks

SQL

Python

Microsoft Fabric

Azure

Education

Bachelor's degree in Computer Science, Data Engineering, Analytics, or a related field

Tools

Power BI

Azure Data Factory

Job description

Location: Atlanta, GA (Hybrid preferred; Remote considered for strong candidates)

Employment Type: Full-Time, On Site

Position Overview

Our client, a leading organization in the oil and gas industry, is seeking a Data Analytics / Data Engineer to support enterprise-scale data initiatives focused on operational efficiency, production optimization, and business intelligence. This role will sit at the intersection of data engineering and analytics, building scalable data pipelines and enabling advanced reporting and insights across the organization.

The ideal candidate has strong experience with Databricks and at least 1 year of hands-on experience with Microsoft Fabric, including Lakehouse architectures, data integration, and analytics workloads.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes using Databricks and cloud-native tools
• Develop and optimize data models to support analytics, reporting, and downstream consumption
• Leverage Microsoft Fabric (Data Factory, Lakehouse, OneLake) to ingest, transform, and manage enterprise data
• Partner with business analysts, data scientists, and stakeholders to understand data requirements and deliver actionable insights
• Ensure data quality, governance, security, and performance across all data platforms
• Support analytics use cases related to operations, supply chain, production, and financial reporting within an oil and gas environment
• Monitor and troubleshoot pipeline failures and performance bottlenecks
• Document data workflows, models, and best practices

Required Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Analytics, or a related field
• 3+ years of experience in data engineering or analytics-focused roles
• Strong hands-on experience with Databricks (Spark, Delta Lake, notebooks, jobs, workflows)
• At least 1 year of experience with Microsoft Fabric, including:
• Fabric Data Factory or data ingestion tools
• Fabric Lakehouse / OneLake
• Integration with Power BI (a plus)
• Proficiency in SQL and Python
• Experience building and maintaining data pipelines in a cloud environment (Azure preferred)
• Solid understanding of data warehousing, data modeling, and analytics best practices

Preferred Qualifications

• Experience working in Oil & Gas, Energy, Utilities, or Industrial environments
• Familiarity with time-series data, operational data, or sensor/SCADA data
• Experience supporting BI tools such as Power BI or similar platforms
• Exposure to data governance, metadata management, and security frameworks
• Azure certifications (Data Engineer, Fabric, or related) are a plus