Hello,
I hope this email finds you well.
My name is Simran, and I am an IT Recruiter from Empower Professionals Inc. I wanted to reach out regarding Data Architect/Data Engineer-Agentic AI-Atlanta (CGEMJP00359863) Atlanta, GA
Role: Data Architect/Data Engineer-Agentic AI-Atlanta (CGEMJP00359863)
Duration: 12 Months
Work site: Atlanta, GA (Fully Onsite)
Years of exp- 15+
Job Description:
We are looking for an experienced Data Architect / Data Engineer to design, develop, and implement scalable enterprise data solutions. The candidate will work closely with business stakeholders, application teams, data engineers, analytics teams, and cloud/platform teams to translate business requirements into robust data architectures and engineering solutions.
The role requires a strong combination of data architecture, data modeling, ETL/data integration, cloud data platforms, SQL, data warehousing, and data governance expertise.
Key Responsibilities:
Data Architecture & Modeling
- Design scalable and secure enterprise data architectures aligned with business requirements.
- Develop conceptual, logical, and physical data models.
- Design solutions for data warehouses, data lakes and lakehouse architectures.
- Define data architecture principles, standards, patterns, and best practices.
- Evaluate existing data architecture and recommend modernization opportunities.
- Design solutions for structured, semi-structured, and unstructured data.
- Data modeling, governance, integration frameworks, security, scalability, and translating business requirements into technical solutions are commonly identified as core Data Architect responsibilities.
Data Engineering & Integration
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Integrate data from multiple internal and external source systems.
- Develop data transformation and processing solutions for batch and streaming workloads.
- Implement reusable frameworks for data ingestion, transformation, validation, and publishing.
- Optimize data pipelines and database queries for performance and scalability.
- Perform data profiling, cleansing, reconciliation, and data-quality validation.
- Troubleshoot data pipeline failures and production data issues.
- Building and maintaining pipelines, databases, storage systems, and optimizing data processing are core Data Engineer responsibilities.
Cloud & Data Platform
- Design and implement cloud-based data solutions using Google Cloud Platform, AWS, or Azure.
- Work with cloud data warehouses, data lakes, object storage, and distributed processing platforms.
- Support migration and modernization of legacy/on-premise data platforms to cloud-based architectures.
- Design solutions considering scalability, reliability, security, performance, and cost.
Data Governance & Security
- Implement enterprise data standards, metadata management, data lineage, and data-quality practices.
- Ensure appropriate data access controls and security standards are incorporated into solution designs.
- Partner with governance and business teams to establish consistent definitions and standards for enterprise data.
- Governance, security, standards, and cross-team alignment are also established elements of the Data Architect role.
Required Technical Skills
Primary Skills
- Data Architecture
- Data Engineering
- Data Modeling
- SQL
- ETL / ELT
- Data Warehousing
- Cloud Data Platforms: Google Cloud Platform / AWS / Azure
- Data Lake / Lakehouse
- Database design
- Data Integration
- Data Quality
Secondary / Preferred Skills
- Informatica / IICS
- Databricks
- Snowflake
- BigQuery
- Spark / PySpark
- Python
- Kafka or other streaming technologies
- Airflow / Cloud Composer
- DBT
- NoSQL databases
- API-based data integration
- Metadata and data catalog solutions
- CI/CD and DevOps practices
- Git
- Agile / Scrum
Qualifications
- Strong experience in data architecture, data engineering, or enterprise data integration.
- Strong knowledge of relational databases, dimensional modeling, and modern cloud data architectures.
- Hands-on experience designing and implementing complex data pipelines.
- Strong SQL and data-analysis skills.
- Experience translating business requirements into scalable technical solutions.
- Strong understanding of OLTP vs. OLAP, normalized/3NF models, dimensional modeling, Star/Snowflake schemas, and data warehousing concepts.
- Ability to perform architecture reviews and provide technical guidance to engineering teams.
- Excellent analytical, problem-solving, documentation, and communication skills.
- Ability to collaborate effectively with both technical and business stakeholders.
Preferred Experience
- Enterprise-scale cloud migration or data modernization programs.
- Legacy ETL/data warehouse modernization.
- Real-time/streaming data architectures.
- Data governance, metadata management, lineage, and data-quality frameworks.
- Designing data platforms supporting BI, analytics, AI/ML, and GenAI use cases.
