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Teradata Data Architect / Data Engineer

June 6, 2026

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)

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Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

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8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

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This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...