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Senior Data Architect (Hybrid)

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AI Summary

Design and optimize scalable data architectures for enterprise systems, leveraging cloud platforms and modern data platforms. Lead data modeling, integration, and governance initiatives while ensuring high performance and security. Requires 10+ years of expertise in relational databases, SQL, and distributed systems with hands-on experience in cloud environments.

Key Highlights
10+ years of experience in data architecture, engineering, and database development
Hands-on expertise in relational databases (Oracle, SQL Server, PostgreSQL, MySQL) and cloud platforms (AWS, Azure, GCP)
Leadership in designing APIs, ETL/ELT pipelines, and scalable data architectures for enterprise applications
Key Responsibilities
Design and implement scalable data architectures, including data warehousing, data lakes, and lakehouse architectures
Develop and optimize ETL/ELT pipelines for large-scale data integration across enterprise applications
Ensure data governance, security, and quality through metadata management and compliance frameworks
Technical Skills Required
SQL Amazon Web Services Data Warehousing
Benefits & Perks
Visa sponsorship required
Nice to Have
Python
Apache Spark
Infrastructure-as-code and cloud automation

Job Description


HYBRID - Atlanta GA


Only W2 - No Corp to Corp


Open to Sponsorship



Required Skills & Experience

  • 10+ years of experience in data architecture, data engineering, database development, or related areas.
  • Strong expertise in data modeling, database architecture, and enterprise data architecture.
  • Hands-on experience with relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.
  • Strong SQL skills and experience with large-scale data environments.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Experience with modern data platforms such as Snowflake, Databricks, BigQuery, Azure Synapse, or Redshift.
  • Strong knowledge of ETL/ELT and data integration technologies.
  • Experience with data warehousing, data lakes, and lakehouse architectures.
  • Knowledge of data governance, data quality, metadata management, and data security.
  • Experience designing APIs and integrating data across enterprise applications.
  • Strong understanding of distributed systems and scalable data architectures.
  • Experience with Agile/Scrum development methodologies.
  • Excellent communication, analytical, and problem-solving skills.

Preferred Skills

  • Experience with Python, Java, or Scala.
  • Experience with Apache Spark, Kafka, Airflow, or similar technologies.
  • Experience with CI/CD and DevOps practices.
  • Knowledge of streaming and real-time data architectures.
  • Experience with master data management (MDM).
  • Familiarity with Data Mesh, Data Fabric, or modern lakehouse architecture.
  • Experience with infrastructure-as-code and cloud automation.
  • Relevant cloud or data architecture certifications are a plus.



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