Data Engineer
Role Overview
The Electric Operations Technology Solutions (EOTS) Data Engineer is responsible for building, operationalizing, and maintaining data pipelines to support data, analytics, and AI use cases across hybrid and multi-cloud environments.
The role involves translating data into consumable formats, supporting various data integration styles (e.g., virtualization, replication, streaming), and ensuring data reliability and scalability.
The data engineer will lead standardization of data curation, data taxonomy and solution delivery across the Electric Operations Technology Solutions Organization for the Databricks and Azure environments.
The position is on the Electric Operations Technology Solutions Leadership Team engaging in strategic delivery of business solutions supporting multiple business areas within Southern Company.
Onsite 4 days per week/ 1 day per week remote
Key Skills for This Role
Full Job Posting
Skills:
- Proficiency in data modeling, access, storage, and quality tools
- Familiarity with Agile, DevOps, CI/CD methodologies
- Strong communication and collaboration skills
- Ability to lead and mentor others
- Familiarity with performance optimization and data governance
- Proactive in sharing knowledge and best practices
- Hands-on expertise with Databricks, SQL, Python, and Apache Spark.
- Proficiency in data modeling for analytics and machine learning.
- MAJOR JOB RESPONSIBILITIES: Specify major duties performed by the job and % of time spent on duties.
- Design and develop methods to process structured, semi-structured, and unstructured data using batch and real-time techniques
- Develop release pipelines to automate build, version control, and deployment tasks
- Build and maintain reusable templates, code libraries, and semantic models
- Establish gatekeeping and guard rail processes for production data promotion
- Collaborate with cross-functional teams including data, business, and technical stakeholders
- Promote data reusability and modular data product delivery
- Define and enforce data quality and integrity controls
- Provide technical guidance to less experienced data engineers
- Optimize performance using parallel processing and minimal data movement
- Stay current with data technologies and share insights across the organization
- Standardize, design, and develop Databricks applications, data integrations and automated business processes.
- Integrate data from multiple systems, databases, APIs, and business applications.
- Provide technical guidance, knowledge sharing, and support for business users and fellow data engineers.
Qualifications
- (Education, Experience, Knowledge, Skills )
- Bachelor’s degree in Computer Science, Engineering, Machine Learning, or related field
- 9+ years of experience in data engineering or related roles
- Experience with batch and real-time data processing frameworks
- Experience with big data technologies (e.g., Hadoop, HIVE, Spark)
- Experience with AI/ML solutions in Python
- 4+ years with on-prem tools (e.g., MSBI, Informatica, Oracle Golden Gate, SQL Server)
- 2+ years with Microsoft Azure tools (e.g., Data Lake, Data Factory, Databricks, Synapse, Power BI)
- Experience with containerization (e.g., Docker, OpenShift)
- Proficiency in data modeling, access, storage, and quality tools
- Familiarity with Agile, DevOps, CI/CD methodologies
- Strong communication and collaboration skills
- Ability to lead and mentor others
- Familiarity with performance optimization and data governance
- Proactive in sharing knowledge and best practices
- Hands-on expertise with Databricks, SQL, Python, and Apache Spark.
- Proficiency in data modeling for analytics and machine learning.
- MAJOR JOB RESPONSIBILITIES: Specify major duties performed by the job and % of time spent on duties.
- Design and develop methods to process structured, semi-structured, and unstructured data using batch and real-time techniques
- Develop release pipelines to automate build, version control, and deployment tasks
- Build and maintain reusable templates, code libraries, and semantic models
- Establish gatekeeping and guard rail processes for production data promotion
- Collaborate with cross-functional teams including data, business, and technical stakeholders
- Promote data reusability and modular data product delivery
- Define and enforce data quality and integrity controls
- Provide technical guidance to less experienced data engineers
- Optimize performance using parallel processing and minimal data movement
- Stay current with data technologies and share insights across the organization
- Standardize, design, and develop Databricks applications, data integrations and automated business processes.
- Integrate data from multiple systems, databases, APIs, and business applications.
- Provide technical guidance, knowledge sharing, and support for business users and fellow data engineers.
About Southern Company Services
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