Job Summary
We are looking for an experienced Data Architect to design and lead enterprise data architecture, data platforms, and data solutions. The ideal candidate will have strong expertise in data modeling, data warehousing, data lakes/lakehouses, cloud data platforms, data integration, governance, and analytics architecture.
The Data Architect will work closely with business stakeholders, data engineers, analysts, application teams, and technology leadership to build scalable, secure, reliable, and high-performing data ecosystems.
Key Responsibilities
- Define and implement enterprise data architecture aligned with business and technology strategy.
- Design scalable architectures for data warehouses, data lakes, lakehouses, and modern data platforms.
- Develop conceptual, logical, and physical data models.
- Define enterprise standards for:
- Data modeling
- Data integration
- Data quality
- Metadata management
- Data governance
- Master Data Management (MDM)
- Data security and privacy
- Design ETL/ELT and real-time data integration architectures.
- Architect batch and streaming data pipelines using technologies such as Kafka, Spark, or equivalent platforms.
- Design cloud-native data solutions across AWS, Azure, or GCP.
- Evaluate and select appropriate databases, storage technologies, integration tools, and data platforms.
- Design architectures for structured, semi-structured, and unstructured data.
- Establish data architecture patterns for analytics, BI, reporting, and AI/ML workloads.
- Work with data engineering teams to ensure architectural standards are followed.
- Define strategies for data migration, modernization, integration, and platform transformation.
- Design highly available, scalable, secure, and cost-efficient data platforms.
- Establish data lineage, metadata, cataloging, and governance capabilities.
- Identify and address data quality, performance, security, and scalability issues.
- Conduct architecture reviews, technology evaluations, and proof-of-concepts.
- Create architecture diagrams, technical standards, reference architectures, and design documentation.
- Provide technical leadership and mentorship to data engineers and other technical teams.
Required Technical Skills
- Strong experience in Data Architecture and Enterprise Architecture.
- Excellent knowledge of data modeling:
- Dimensional modeling
- Star/snowflake schemas
- 3NF
- Data Vault
- Canonical data models
- Strong experience with Data Warehousing and Data Lakes/Lakehouses.
- Hands-on experience with technologies such as:
- Snowflake
- Databricks
- Azure Data Factory / AWS Glue / equivalent
- Apache Spark
- Kafka / streaming technologies
- Strong SQL and database knowledge.
- Experience with relational databases such as Oracle, SQL Server, PostgreSQL, MySQL, etc.
- Experience with NoSQL databases is a plus.
- Strong understanding of ETL/ELT, APIs, CDC, batch processing, and real-time data integration.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Knowledge of data governance, data quality, metadata, lineage, security, and privacy.
- Understanding of BI and analytics platforms such as Power BI, Tableau, or equivalent.
- Experience with DevOps, CI/CD, infrastructure automation, and cloud-native technologies is preferred.
Compensation, Benefits and Duration
Minimum Compensation: USD 53,000
Maximum Compensation: USD 188,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post.
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