Capgemini is hiring a Data Architect/Data Engineer for an onsite contract role in Atlanta, GA 30305. You’ll help design and deliver scalable enterprise data platforms, including modern lakehouse and warehouse architectures, with an emphasis on performance, security, and data quality. This role supports a contract engagement with an hourly rate of USD 48 to 75 per hour.
What you’ll do
- Design scalable and secure enterprise data architectures aligned with business requirements.
- Create conceptual, logical, and physical data models to support enterprise reporting and analytics needs.
- Design target solutions for data warehouses, data lakes, and lakehouse architectures.
- Define data architecture principles, standards, patterns, and best practices for consistent delivery.
- Assess existing data architectures and recommend modernization opportunities.
- Design solutions for structured, semi-structured, and unstructured data.
- Build and maintain ETL/ELT pipelines that support both batch and streaming workloads.
- Integrate data from multiple internal and external source systems, using reusable ingestion and transformation frameworks.
- Implement reusable components for data ingestion, transformation, validation, and publishing.
- Optimize pipelines and database queries for performance and scalability.
- Support data profiling, cleansing, reconciliation, and data-quality validation.
- Troubleshoot pipeline failures and production data issues to maintain reliability.
- Design and implement cloud-based data solutions using GCP, AWS, or Azure, including warehouses, lakes, object storage, and distributed processing.
- Plan and support migration and modernization of legacy or on-premise data platforms to cloud architectures.
- Design for scalability, reliability, security, performance, and cost.
- Implement enterprise standards for metadata management, data lineage, and data-quality practices.
- Ensure solution designs include appropriate data access controls and security standards.
- Partner with governance and business teams to establish consistent enterprise data definitions and standards.
- Provide technical guidance to engineering teams through architecture reviews.
Skills and experience
- 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.
- Ability to translate business requirements into scalable technical solutions.
- Understanding of OLTP vs. OLAP, normalized/3NF models, dimensional modeling, Star/Snowflake schemas, and data warehousing concepts.
- Capability to perform architecture reviews and guide engineering teams.
- Excellent analytical, problem-solving, documentation, and communication skills.
- Experience collaborating with technical and business stakeholders.
Technologies you may work with
SQL, ETL/ELT, GCP, AWS, Azure, Data Lake / Lakehouse, Informatica / IICS, Databricks, Snowflake, BigQuery, Spark / PySpark, Python, Kafka, Airflow / Cloud Composer, DBT, NoSQL databases, API-based data integration, metadata and data catalog solutions, CI/CD and DevOps, Git, Agile / Scrum.
Benefits
- Medical
- Dental
- Vision and retirement benefits
Preferred
- 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.
- Enterprise-scale cloud migration or data modernization programs.
- Legacy ETL/data warehouse modernization and real-time/streaming data architectures.
- Experience with data governance, metadata management, lineage, and data-quality frameworks.
- Designing platforms supporting BI, analytics, AI/ML, and GenAI use cases.
