Data Engineer (Application/Solutions Architect)

Job Title : Applic / Solutions Architect, Sr. (Data Engineer)

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Location : GPC Corporate HQ, Atlanta

Department Name : GPC4020 - PD Data Analytics & Innovation

This position is responsible for translating data into readily consumable forms to deliver integrated data to consumers by building, operationalizing, and maintaining data pipelines for Data & Analytics use cases across heterogeneous environments.

The Data Engineer also plays a role in working with various data integration tools which support combination of data delivery styles such as virtualization, data replication, messaging and streaming in hybrid and multi-cloud integration scenarios.

The position is responsible for detailed data analysis, data modeling and requirements mapping, and ETL design and development.

They also work closely with Data Architects within the organization to ensure that new analytics solutions align with the enterprise data management and Power Delivery data strategy.

This includes identification of the true source of data, reducing data redundancy and focus on increased integration of data across business units.

Responsibilities

• Designing and Developing methods to process structured, semi-structured, and unstructured data using batch and real-time data processing techniques.
• Delivering fast, reliable, and scalable data by incrementally and efficiently processing as it arrives from files or streaming sources like Kafka, DBMS and NoSQL.
• Developing Release pipelines to automate recurring manual tasks like creating a build package, checking that build package into a version control repository and deploys it to a DV / UA environment.
• Building and Maintaining templates such as code libraries, pipeline patterns and semantic models to promote reuse and agility.
• Establishing gatekeeping processes that monitors and controls the promotion of successful data processes into production by understanding the business criticality.
• Collaborating with cross-functional teams with a combination of data, business, and technical personas, as well as a product owner / manager as necessary.
• Advocating data reusability by breaking down monolithic data delivery processes into modular data product delivery.
• Ensuring data reliability by defining data quality and integrity controls within the pipeline with defined data expectations and addressing data quality errors with predefined policies.
• Actively working with less experienced data engineers providing technical guidance and oversight.
• Understanding the usage of performance optimization clusters that parallelize jobs and minimize the data movement in Batch and stream data processing.
• Recommending improvements to the processes, technology, and interfaces that reduce the development time and effort and enhance the effectiveness of the team.
• Promptly participating in the Enterprise Social Networking sites, staying up to date on new data technologies and best practices and shares insights with others in the organization.

Candidates with the following preferred qualifications are encouraged to apply :

Education

Bachelor’s degree required; degree in technical field such as computer science, engineering, mathematics, or another relevant academic discipline. Advanced degree preferred.

Knowledge, Skills, and Abilities

• Working experience with batch and real-time data processing frameworks.
• Working experience with data modelling, data access, schemas, and data storage techniques.
• Working experience with data quality tools.
• Experience in creating functional and technical designs for data engineering and analytics solutions.
• Experience implementing data models of different schemas and working with diverse data source types.
• Hands-on experience developing solutions with big data technologies such as Hadoop, HIVE and Spark.
• Hands-on experience developing and supporting statistical models, R, and / or Python based AI / ML solutions.
• 5+ years hands-on experience designing, developing, testing, deploying, and supporting data engineering and analytics solutions using on-premise tools such as MSBI (SSIS / SSAS), Informatica, Oracle Golden Gate, SQL, Oracle, and SQL Server.
• 3+ years hands-on experience designing, developing, testing, deploying, and supporting data engineering and analytics solutions using Microsoft cloud-based tools such as Azure Data Lake, Azure Data Factory, Azure Databricks, Python, Azure Synapse, Azure Key Vault, and Power BI.
• Experience with Containerization methodologies Docker, OpenShift etc.
• Experience with Agile as well as DevOps, CI / CD methodologies.
• Hands-on experience designing and developing solutions involving data sourcing, enrichment and delivery using APIs & Web Services.

Georgia Power is the largest electric subsidiary of Southern Company (NYSE : SO), America's premier energy company. Value, Reliability, Customer Service and Stewardship are the cornerstones of the Company's promise to 2.

6 million customers in all but four of Georgia's 159 counties. Committed to delivering clean, safe, reliable, and affordable energy at rates below the national average, Georgia Power maintains a diverse, innovative generation mix that includes nuclear, coal and natural gas, as well as renewables such as solar, hydroelectric and wind.

Southern Company (NYSE : SO) is a leading energy provider serving 9 million residential and commercial customers across the Southeast and beyond through its family of companies.

Providing clean, safe, reliable and affordable energy with excellent service is our mission.

Southern Company is an equal opportunity employer where an applicant's qualifications are considered without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or any other basis prohibited by law.

Job Identification : 7961

Job Category : Data Analytics

Job Schedule : Full time

Company : Georgia Power

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