Data Architect

Raas Infotek LLC

Dallas, United States

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Query Performance Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Business Analytics Applications Microsoft Azure Batch Processing BigQuery Cloud Computing Continuous Integration Data Architecture Information Engineering

+46 more

Data Governance Data Infrastructure Data Integration Extract Transform Load (ETL) Data Migration Data Security Data Systems Data Warehousing Database Applications Relational Databases Database Development DevOps Dimensional Modeling Python (Programming Language) PostgreSQL Metadata Meta-Data Management Microsoft SQL Server MySQL Oracle (Applications) Cloud Services SQL Databases Data Streaming Data Processing Google Cloud Enterprise Software Applications Cloud Platform System Snowflake Apache Spark Multi-Cloud Database Performance Event Driven Architecture Microsoft Fabric Data Lakes Pyspark Infrastructure Automation Frameworks Data Lineage Collibra Apache Kafka Data Management Physical Data Models Video Streaming Azure Synapse Analytics Data Pipelines Amazon Redshift Databricks

Job description

We are seeking an experienced Data Architect to design, develop, and implement scalable enterprise data architectures supporting modern analytics, reporting, cloud, and data-driven applications. The ideal candidate will have strong experience with data modeling, cloud data platforms, data integration, governance, and enterprise data architecture., * Design and implement scalable enterprise data architectures across on-premises and cloud environments.

Develop conceptual, logical, and physical data models for enterprise applications and analytics platforms.
Define data architecture standards, patterns, principles, and best practices.
Design modern data warehouses, data lakes, and lakehouse architectures.
Develop and optimize data pipelines and ETL/ELT processes.
Work with cloud data platforms such as AWS, Azure, or Google Cloud Platform.
Design solutions using platforms such as Snowflake, Databricks, Redshift, BigQuery, or Azure Synapse.
Develop data integration strategies using APIs, batch processing, streaming, and event-driven architectures.
Implement data governance, data quality, metadata management, lineage, security, and compliance frameworks.
Design highly available, scalable, secure, and cost-effective data solutions.
Collaborate with Data Engineers, Data Scientists, Business Analysts, Application Architects, Cloud Architects, and DevOps teams.
Analyze existing data environments and develop modernization and migration strategies.
Optimize database performance, query performance, storage, and data processing.
Create architecture diagrams, technical documentation, data models, and design specifications.
Provide technical leadership and mentor data engineering and development teams.

Requirements

10+ years of experience in data architecture, data engineering, database development, or related roles.
Strong experience with enterprise data architecture and data modeling.
Expertise in SQL and relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.
Strong knowledge of ETL/ELT and data integration.
Experience designing Data Warehouse, Data Lake, and Lakehouse architectures.
Strong experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, Redshift, BigQuery, or Azure Synapse.
Experience with Python, Spark, or similar data processing technologies.
Strong understanding of data governance, data security, metadata, data quality, and data lineage.
Experience with enterprise-scale data migration and modernization projects.
Strong knowledge of dimensional modeling, star/snowflake schemas, and normalization/denormalization.
Excellent troubleshooting, analytical, communication, and problem-solving skills., * Experience with Snowflake and Databricks.
Experience with Apache Spark / PySpark.
Experience with real-time/streaming technologies such as Kafka.
Experience with AWS, Azure, and Google Cloud Platform multi-cloud environments.
Experience with Data Governance and Master Data Management (MDM).
Experience with tools such as Collibra, Alation, Informatica, or Microsoft Purview.
Knowledge of Data Mesh and Data Fabric architectures.
Experience with CI/CD, DevOps, and Infrastructure as Code.
Experience with AI/ML data platforms and analytics environments.