Senior Data Architect

A Senior Data Architect at Anderson Merchandisers will design, build, and continuously improve the architecture underlying our analytics and transactional data platforms. This senior-level, individual-contributor role reports to the Director of Information Systems and is expected to set technical direction and standards that the broader Software Development team follows, rather than manage people day-to-day. They will lead the design of our Google BigQuery analytics data warehouse-defining schema, partitioning and clustering strategy, and data modeling standards that support reporting, dashboards, and ad hoc analysis across the business. They will also serve as the senior technical advisor on our Google Cloud Spanner database layout as we consolidate our MySQL and Microsoft SQL Server transactional systems onto Spanner as our new system of record, consulting with development teams on schema design, indexing strategy, and scalability. They will partner with the Software Development Manager, Software Developers, ETL/Data Pipeline developers, analysts, and business stakeholders to ensure data is modeled consistently, efficiently, and securely across our Dash Management (PHP web UI), ETL, Salesforce, Workday, Dash Execution (Flutter mobile UI), and BigQuery - our analytics reporting destination and Spanner (alongside MySQL and Microsoft SQL Server during the consolidation) as our primary transactional source systems. They will design and develop our medallion (bronze/silver/gold) data architecture in BigQuery and build the ETL/ELT pipelines needed to move and transform data from these source systems through each layer. They will serve as the primary liaison between the Information Systems department and the Analytics team, translating analytics reporting needs into IS-supported data architecture and keeping both groups aligned as requirements evolve. What would you do in this role? Responsibilities and Duties - Designing and maintaining the BigQuery analytics data warehouse layout, including dataset organization, table schema, partitioning, and clustering strategies to optimize query performance and cost. - Designing and developing a medallion (bronze/silver/gold) data architecture within BigQuery, defining the structure and quality standards for each layer. - Writing and maintaining the ETL/ELT pipelines needed to move and transform data from Spanner, Salesforce, and Workday (and MySQL/Microsoft SQL Server during the consolidation) into BigQuery's bronze, silver, and gold layers. - Consulting with development teams on Cloud Spanner database schema design, indexing, and interleaving strategy as our system of record, so it can support both transactional workloads and clean, reliable extraction into BigQuery. - Advise on the consolidation of MySQL and Microsoft SQL Server transactional data onto Spanner, ensuring the resulting schema supports efficient downstream ETL/ELT into BigQuery. - Defining and enforcing data modeling standards and naming conventions across analytics and operational databases. - Reviewing proposed schema changes across systems for downstream impact on reporting, analytics, and reconciliation processes. - Collaborating with business stakeholders and analysts to translate reporting requirements into sound, scalable data models. - Acting as the primary liaison between the Information Systems department and the Analytics team, facilitating regular communication and ensuring analytics needs are reflected in IS-supported data architecture. - Evaluating and recommending tools, patterns, and best practices for data governance, data quality, and cost optimization within Google Cloud Platform. - Supporting the ongoing evaluation of a modern, AI-assisted BI frontend to replace Oracle Analytics Cloud, and implementing the BigQuery-side data structures and access needed to support that tool once a selection is made. - Documenting data architecture, lineage, and schema design decisions for use by engineering and analytics teams. - Troubleshooting performance issues related to query design, indexing, and schema in both BigQuery and Spanner. - Staying current on Google Cloud Platform (BigQuery, Spanner) features and advising on adoption where it benefits the organization. - Mentoring Software Developers on data modeling and query design best practices, and reviewing their schema changes prior to release. - Advising the Software Development Manager and Director of Information Systems on data architecture strategy, technical risk, and long-term platform direction. - Other Duties - Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. Required Qualifications - 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 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 (dimensional modeling, normalization/denormalization trade-offs) for analytics use cases. - Familiarity with Google Cloud Platform services and IAM/data governance practices. - Strong problem-solving and analytical skills. - Strong communication skills, with the ability to explain architectural trade-offs to both 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 to communicate architectural recommendations clearly to management and department leadership. Preferred - Bachelor's Degree in Computer Science, Data Engineering, or related field. IND-123