Teradata Data Architect / Data Engineer

We are seeking a senior Teradata Data Architect / Data Engineer to lead the design, development, and optimization of enterprise data warehouse, data integration, and modern data platform solutions for a California state agency. The role owns the data architecture vision — data modeling, ETL/ELT and big-data pipelines, performance tuning, and data governance — while serving as the senior technical authority guiding development teams and state stakeholders through the full project and approval lifecycle. Public sector data warehousing experience and familiarity with California Department of Technology (CDT) project frameworks are strongly preferred.

Key Responsibilities

• Define and own the overall data architecture across the enterprise Teradata warehouse and modern lakehouse/cloud platforms, including logical/physical data models, schema design, and data layer strategy
• Design and develop scalable ETL/ELT and big-data pipelines to ingest, transform, and integrate data from multiple source and legacy state systems
• Build and optimize data pipelines on Databricks / Apache Spark (PySpark, Spark SQL), including Delta Lake and lakehouse/medallion architecture
• Develop, optimize, and tune complex Teradata SQL, BTEQ, stored procedures, macros, and views for performance and scalability
• Architect data integration using Teradata utilities (FastLoad, MultiLoad, TPT, FastExport, TPump) and modern ingestion frameworks
• Design and implement batch and streaming data pipelines (e.g., Kafka, Spark Structured Streaming, Auto Loader)
• Build and manage workflow orchestration (e.g., Apache Airflow, Databricks Workflows, Azure Data Factory)
• Lead performance optimization — query tuning, indexing/PPI strategy, statistics collection, workload management (TASM), Spark cluster/job tuning, and capacity planning
• Define data quality, profiling, cleansing, and master/reference data management approaches
• Design data migration, conversion, and transformation strategies for legacy-to-target and on-prem-to-cloud transitions
• Establish data governance, metadata management, and data lineage practices (e.g., Unity Catalog, Collibra, or comparable)
• Build and maintain data dictionaries, source-to-target mappings, and technical specifications
• Apply CI/CD and DevOps/DataOps practices to data pipelines (Git, automated testing, deployment automation)
• Collaborate with project managers, business analysts, BI/reporting teams, developers, and QA throughout the SDLC
• Support cloud data migration/modernization efforts (e.g., Teradata Vantage, or migration to cloud lakehouse/warehouse platforms) as required
• Support procurement and solution-evaluation activities, including reviewing SOWs, technical requirements, and vendor proposals
• Provide technical leadership through testing, UAT, deployment, and post-go-live stabilization; mentor and transfer knowledge to state staff

Required Qualifications

• Bachelor''''''''''''''''''''''''''''''''s degree in Computer Science, Information Technology, or related field (equivalent additional experience may substitute)
• 8+ years of data engineering / data warehousing experience, with 5+ years hands-on with Teradata
• Deep expertise in Teradata architecture, advanced SQL, and the platform''''''''''''''''''''''''''''''''s performance and parallelism concepts (AMPs, PI/PPI, partitioning)
• Strong hands-on background with Teradata utilities (FastLoad, MultiLoad, TPT, FastExport, BTEQ, TPump)
• Hands-on experience building data pipelines with Databricks and/or Apache Spark (PySpark, Spark SQL)
• Strong Python (and SQL) development skills for data engineering and automation
• Proven experience in dimensional and 3NF data modeling for enterprise data warehouses
• Strong ETL/ELT development experience (e.g., Informatica, DataStage, Talend, Ab Initio, or comparable)
• Experience leading data migration and conversion on large, complex implementations
• Strong performance tuning, query optimization, and workload management experience
• Demonstrated experience as the lead data architect/engineer on at least one large, complex, enterprise-scale data initiative

Preferred Qualifications

• Prior data warehouse / data engineering delivery with a California state agency or other U.S. public sector / government organization
• Familiarity with the CDT Project Approval Lifecycle (PAL) / Project Delivery Lifecycle (PDL) and the California Project Management Framework (CA-PMF)
• Experience with Databricks Lakehouse Platform (Delta Lake, Unity Catalog, Databricks SQL, Workflows)
• Experience with cloud data platforms (AWS — Redshift, Glue, EMR, S3; Azure — Synapse, Data Factory, ADLS; Google Cloud Platform — BigQuery, Dataflow; Snowflake)
• Experience with Teradata Vantage and/or cloud migration of legacy Teradata warehouses
• Streaming and messaging experience (Apache Kafka, Spark Structured Streaming, Kinesis, Event Hubs)
• Workflow orchestration (Apache Airflow, Databricks Workflows, dbt)
• Data modeling tooling (Erwin, ER/Studio) and BI/reporting tools (Tableau, Power BI, MicroStrategy)
• Infrastructure-as-code and containerization exposure (Terraform, Docker) for data platforms
• Teradata, Databricks (Certified Data Engineer Associate/Professional), and/or cloud data certifications (AWS, Azure, Google Cloud Platform, Snowflake)