Principal Data Architect III

CO Salary Range: USD 138,800.00 - 246,400.00 per year

JOB SUMMARY

We are seeking a highly experienced Senior Data Architect to design, optimize, and govern scalable, secure, and high-performance data architectures for complex, distributed, and multi-modal environments. This individual will serve as the principal architect responsible for data platform blueprinting, modeling, and system interoperability across OLTP, OLAP, real-time, and AI/ML pipelines. The ideal candidate combines deep technical knowledge with system-level thinking and has proven expertise across modern data stack technologies, cloud-native and edge-cloud platforms, and data governance frameworks. Work to include data extraction, transformation, loading, integration in support of enterprise data infrastructures, data warehouse, operational data stores and master data management.

• Actively and consistently supports all efforts to simplify and enhance the customer experience.
• Lead the implementation of data services and data movement infrastructures.
• Architect data structures/models and data movement infrastructures across organizations.
• Lead the implementation of programming concepts such as data structures, error handing, data manipulation and I/O processing.
• Re-design of jobs based on job failures across organization, including but not limited to error handling, data manipulation and I/O processing.
• Lead the implementation of database concepts and practices including definition and query language.
• Architect the implementation of database concepts and practices including definition and query language across the organization.
• Design, implement, monitor, enhance, and troubleshoot requirements and architecture specifications of data warehousing systems and/or processing infrastructure.
• Lead enterprise wide teams to design, implement, and support end-to-end data solutions across multiple platforms, environments, domains, and locations.
• Provides leadership and innovation for development of ETL processes, programs and solutions as per established standards across supported organizations.
• Monitor and administer automated and manual data integration and ETL jobs to verify execution and measure performance.
• Mentor and guide junior developers, vendors, consultants, and external partners to quickly identify and resolve data integration and ETL job issues.
• Diagnose the most intricately complex issues and evaluates, recommends, and executes the best resolution.
• Influence the overall data insights program.
• Deliver quality results to the data development team.
• Ensure alignment to drive consistency and global solutions.
• Lead collaborations with business and technical teams.
• Develop and document best practices.
• Provide leadership to fellow team members on new and existing data development standards, expectations, and trends.

• Bachelor's degree or equivalent experience

• Ten (10+) years of ETL experience
• Eight (8+) years of Experience with SQL, Shell Script, Python, JSON
• Seven (7+) years of Data integration experience
• Seven (7+) years of Data visualization experience (Tableau, Alterx, Microstrategy)
• Seven (7+) years of Software engineering experience
• Extensive experience with designing or architecting for the most intricately complex ETL processing and warehousing

• Extensive experience with building use cases and providing development support to data scientists
• Extensive with building use cases and providing development support to data engineers
• Extensive experience with data lake - all data sources - building out data sets for uses cases
• Extensive experience with building SQL/HIVE databases and tables
• Extensive experience with querying and designing efficient warehousing structures
• Master expert knowledge of data access methods from relational databases using SQL
• Master expert knowledge of and hands on with web services (WSDL Soap, Restful) to access data from various source systems
• Master expert knowledge of FTP/sFTP
• Effective written and verbal communication skills
• Effective analytical and troubleshooting abilities

• Ability to read, write, speak and understand English

• Data Modeling & Semantics
  Covers conceptual, logical, and physical models (3NF, Star, Vault), plus semantic layers using RDF/OWL, SPARQL, and MDM strategies for metadata, golden records, and ontologies.
• Data Storage & Persistence
  Spans relational (PostgreSQL, Oracle), columnar (Snowflake, Redshift), NoSQL (MongoDB, Cassandra), time-series (InfluxDB), graph (Neo4j), and vector databases (Pinecone, Faiss).
• Data Ingestion & Integration
  Includes batch (NiFi, dbt), streaming (Kafka, Flink), CDC (Debezium), ETL tools (Talend, Matillion), and API-driven methods (REST, GraphQL, gRPC).
• Edge Data Fabric & Distributed Systems
  Focuses on edge-to-cloud data flow (MQTT, Kafka), analytics at the edge (Jetson, TensorRT), coordination systems (Zookeeper, Consul), and frameworks like EdgeX Foundry and KubeEdge.
• Data Processing & Compute Frameworks
  Highlights big data engines (Spark, Trino), serverless (Lambda, GCF), GPU analytics (RAPIDS, BlazingSQL), and geospatial platforms (PostGIS, GeoMesa).
• Cloud & Hybrid Architecture
  Details cloud-native services (Redshift, Synapse, BigQuery), lakehouses (Delta Lake, Iceberg), IaC tools (Terraform, CDK), and multi-cloud patterns (federation, compliance zoning).
• DataOps, Governance & Security
  Encompasses CI/CD for data (Airbyte, dbt), orchestration (Airflow, Dagster), governance (Data Mesh, DAMA), privacy techniques (differential privacy), and lineage tools (OpenLineage).
• AI/ML & Analytics Enablement
  Supports ML pipelines (Feast, MLflow), real-time model serving (Triton, TorchServe), BI tools (Looker, Tableau), scripting languages (SQL, Python), and advanced paradigms like Data Mesh and TEEs.

• Master's preferred, or equivalent experience with design, architecture, and leadership