Senior Data Architect

Anderson Merchandisers•Plano, TX

20h

About The Position

The Senior Data Architect is a senior-level individual-contributor role at Anderson Merchandisers, reporting to the Director of Information Systems. The role designs, builds, and continually improves the architecture for analytics and transactional data platforms, setting technical direction and standards for the Software Development team without managing employees day to day. The role leads the design of the Google BigQuery analytics warehouse, including schema, partitioning, clustering, and data modeling standards. It also advises development teams on Google Cloud Spanner database design as MySQL and Microsoft SQL Server transactional systems are consolidated onto Spanner. The architect partners with Software Development, ETL/Data Pipeline developers, analysts, and business stakeholders to model data consistently, efficiently, and securely across company systems. The role develops a bronze/silver/gold medallion data architecture in BigQuery and the ETL/ELT pipelines that move and transform data from source systems. It is also the primary liaison between Information Systems and Analytics, translating reporting requirements into IS-supported data architecture and keeping the teams aligned as requirements change.

Requirements

At least 7 years of experience designing and maintaining data warehouse or analytics database architectures.
Expert knowledge of SQL and relational database design principles.
Hands-on experience with Google BigQuery, including schema design, partitioning, clustering, and query optimization.
Experience with Google Cloud Spanner or another distributed/NewSQL database used as a transactional (OLTP) system.
Hands-on experience building ETL/ELT pipelines with tools such as Apache Hop, Google Cloud Dataflow, or Pentaho Kettle.
Experience designing medallion (bronze/silver/gold) or similar layered data architectures.
Understanding of data modeling techniques, including dimensional modeling and normalization/denormalization trade-offs for analytics.
Familiarity with Google Cloud Platform services and IAM/data governance practices.
Strong problem-solving and analytical skills.
Strong communication skills and ability to explain architectural trade-offs to technical and non-technical stakeholders.
Ability to work independently and collaboratively across Software Development, ETL, and Analytics teams.
Demonstrated ability to set technical direction and influence engineering decisions without direct management authority, and communicate recommendations to management and department leadership.

Nice To Haves

Bachelor’s degree in Computer Science, Data Engineering, or a related field.

Responsibilities

Design and maintain the BigQuery analytics warehouse layout, including dataset organization, table schemas, partitioning, and clustering strategies to optimize query performance and cost.
Design and develop a bronze/silver/gold medallion architecture in BigQuery, defining the structure and quality standards for each layer.
Write and maintain ETL/ELT pipelines that move and transform data from Spanner, Salesforce, Workday, and, during consolidation, MySQL and Microsoft SQL Server into BigQuery.
Advise development teams on Cloud Spanner schema design, indexing, and interleaving strategy to support transactional workloads and reliable extraction into BigQuery.
Advise on consolidating MySQL and Microsoft SQL Server transactional data onto Spanner, ensuring schemas support efficient downstream ETL/ELT.
Define and enforce data modeling standards and naming conventions across analytics and operational databases.
Review proposed schema changes across systems for downstream effects on reporting, analytics, and reconciliation.
Collaborate with business stakeholders and analysts to turn reporting requirements into scalable data models.
Serve as the primary liaison between Information Systems and Analytics, facilitating communication and ensuring analytics needs are reflected in IS-supported data architecture.
Evaluate and recommend tools, patterns, and practices for data governance, data quality, and cost optimization in Google Cloud Platform.
Support evaluation of an AI-assisted BI frontend to replace Oracle Analytics Cloud, and implement supporting BigQuery data structures and access after a tool is selected.
Document data architecture, lineage, and schema design decisions for engineering and analytics teams.
Troubleshoot query, indexing, and schema performance issues in BigQuery and Spanner.
Stay current on Google Cloud Platform features, including BigQuery and Spanner, and advise on adoption where beneficial.
Mentor Software Developers on data modeling and query design practices, and review their schema changes before release.
Advise the Software Development Manager and Director of Information Systems on architecture strategy, technical risk, and long-term platform direction.
Perform other duties and activities as assigned; duties may change at any time with or without notice.