Lead Data Architect

Raymond James-posted about 13 hours ago

Full-time • Mid Level

Hybrid • Saint Petersburg, FL

5,001-10,000 employees

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This position follows our hybrid-friendly schedule, so you get the best of both worlds – flexibility and collaboration. In office days will be 2-3 per week averaging 10-12 days per month in our St Petersburg, FL Corporate Office. Job Summary: As a key member of the Enterprise Data & Analytics Architecture team, the Lead Data Architect will design and model enterprise data assets across both on-premises and cloud environments. This role involves collaborating closely with Data Engineering Teams and Enterprise Data Management teams to develop flexible, scalable, and high-performing data solutions. You will advocate for best practices in data architecture, define appropriate data access patterns, and provide strategic technical leadership.

Data Modeling & Performance optimization : Design optimal logical and physical data models using ER Studio or similar tools. Resolve complex database performance, capacity, and replication challenges. Architect and evaluate cloud-based data solutions.
Collaboration : Engage closely with Enterprise Data Management and Engineering teams to deliver robust, scalable, and performant data assets spanning on-prem and cloud environments.
Data Lakehouse : Lead the design and maintenance of data lakehouse solutions on AWS Redshift, Oracle Exadata and Apache Iceberg optimizing for large-scale data volumes
ETL Pipeline Design : Design ETL pipelines to seamlessly move and transform data across medallion architecture layers. Design robust Kafka schemas to enable real time data movement.
Data Management: Collaborate with the Data Management tooling team to integrate comprehensive metadata into the organizations data catalog.
Platform Architecture: Drive strategic selection and optimal use of data tools and technologies across both on-premises and cloud platforms. Advocate and implement best practices for tool adoption and usage.
Data Architecture Influence : Act as a custodian for data modeling guidelines and standards, serving as a Subject Matter Expert (SME) for data architecture throughout the organization. Influence teams to adopt sound architectural practices.
Data Access Strategy : Establish clear data access patterns, partnering closely with data consumers to identify appropriate data sources and recommend optimal tools and technologies for data consumption from data lakehouse and warehouse environments.

Expert level knowledge of Data Architecture, Data Modeling, Data Lake house and data warehouse design methodologies (star schema, snowflake schema, normalization, denormalization).
Proficient with database technologies: Oracle (including RAC, Exadata), SQL Server, AWS Redshift, and replication tools like Oracle Golden Gate and AWS DMS.
Advanced SQL, PL/SQL development, and database performance tuning skills.
Deep expertise in AWS Data Ecosystem—Athena, Iceberg, Lake Formation, Glue, EMR, Sagemaker, S3, Airflow, Aurora, Presto.
Skilled in scripting and automation (Shell, Python).
Expert-level knowledge of various storage formats such as Parquet, Avro, JSON, with the ability to select the appropriate format for each use case.
Ability to architect for real-time (Kafka) and batch processing use cases.
Strong understanding of data management practices and financial services domain.
Ability to create access roles and access guidelines to secure cloud data assets using cloud-native tools such as AWS Lake Formation and Glue.
Good knowledge of analytics and compliance use cases and BI tools such as Tableau, ThoughtSpot, and SageMaker.
Bachelor’s: Business Administration, Bachelor’s: Computer and Information Science (Required), Bachelor’s: Computer Engineering
General Experience – 10 to 15 years

Financial Services experience is preferred.
AWS or a relevant cloud certification is highly preferred.

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