View all jobs
Systems Analyst (hybrid)
14817 - Systems Analyst (hybrid) - Austin, TX
Start Date: ASAP
Type: Temporary Project
Estimated Duration: 12 months with possible extensions
Work Setting: Hybrid. 3 days remote with 2 days (Mondays and Thursdays) required to be onsite at the location listed above.
Only candidates able to relocate as required should apply to avoid removal from future consideration.
Our client is filling this contract position exclusively through approved staffing partners, so this opportunity is not available by applying directly with the client. If you're interested, we'd be happy to represent you throughout the hiring process.
Required:
• Experience with Information Technology (IT), supporting the design, development, deployment, or delivery of technology solutions (8+ years).
• Experience with Databricks, including building and optimizing ETL/ELT data pipelines using Apache Spark (8+ years).
• Experience with Data warehousing and dimensional data modeling (star/snowflake schemas) (8+ years).
• Experience with Structured Query Language (SQL) and Python (or Scala) for large-scale data processing (8+ years).
• Experience with Designing and developing dashboards and applications natively within Databricks (e.g., Databricks SQL dashboards, Databricks Apps) (8+ years).
• Experience with Implementing data governance, data quality, and data security practices (8+ years).
• Experience with Implementing Lakeflow Declarative Pipelines (formerly Delta Live Tables/DLT) for building and managing production data pipelines (8+ years).
• Experience with Delta Lake, medallion architecture (bronze/silver/gold layers), data Lakehouse design, and creating and scheduling offline jobs using Lakeflow Jobs (formerly Databricks Workflows) or similar orchestration tools (e.g., Airflow) (8+ years).
• Excellent communication skills, both verbal and written, including presenting insights to technical and business stakeholders (8+ years).
Preferred:
• Experience with Working in public sector or state government environments (1+ years).
• Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).
• Experience with Continuous Integration/Continuous Deployment (CI/CD) practices for data pipelines (DevOps, Git-based workflows) (1+ years).
Responsibilities:
• Understand business objectives and problems, identify alternative solutions, perform studies and cost/benefit analysis of alternatives.
• Analyze user requirements, procedures, and problems to automate processing or to improve existing computer systems.
• Confer with personnel of organizational units involved to analyze current operational procedures, identify problems, and learn specific input and output requirements.
• Write detailed descriptions of user needs, program functions, and steps required to develop or modify computer programs.
• Review computer system capabilities, specifications, and scheduling limitations to determine if requested program or program change is possible within existing system.
• Design, develop, and optimize scalable data solutions on Databricks, leveraging PySpark or Scala for large-scale data processing.
• Build and maintain ingestion pipelines, Declarative Pipelines (DLT), and Medallion Architecture (Bronze, Silver, Gold) to support enterprise analytics and reporting.
Start Date: ASAP
Type: Temporary Project
Estimated Duration: 12 months with possible extensions
Work Setting: Hybrid. 3 days remote with 2 days (Mondays and Thursdays) required to be onsite at the location listed above.
Only candidates able to relocate as required should apply to avoid removal from future consideration.
Our client is filling this contract position exclusively through approved staffing partners, so this opportunity is not available by applying directly with the client. If you're interested, we'd be happy to represent you throughout the hiring process.
Required:
• Experience with Information Technology (IT), supporting the design, development, deployment, or delivery of technology solutions (8+ years).
• Experience with Databricks, including building and optimizing ETL/ELT data pipelines using Apache Spark (8+ years).
• Experience with Data warehousing and dimensional data modeling (star/snowflake schemas) (8+ years).
• Experience with Structured Query Language (SQL) and Python (or Scala) for large-scale data processing (8+ years).
• Experience with Designing and developing dashboards and applications natively within Databricks (e.g., Databricks SQL dashboards, Databricks Apps) (8+ years).
• Experience with Implementing data governance, data quality, and data security practices (8+ years).
• Experience with Implementing Lakeflow Declarative Pipelines (formerly Delta Live Tables/DLT) for building and managing production data pipelines (8+ years).
• Experience with Delta Lake, medallion architecture (bronze/silver/gold layers), data Lakehouse design, and creating and scheduling offline jobs using Lakeflow Jobs (formerly Databricks Workflows) or similar orchestration tools (e.g., Airflow) (8+ years).
• Excellent communication skills, both verbal and written, including presenting insights to technical and business stakeholders (8+ years).
Preferred:
• Experience with Working in public sector or state government environments (1+ years).
• Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).
• Experience with Continuous Integration/Continuous Deployment (CI/CD) practices for data pipelines (DevOps, Git-based workflows) (1+ years).
Responsibilities:
• Understand business objectives and problems, identify alternative solutions, perform studies and cost/benefit analysis of alternatives.
• Analyze user requirements, procedures, and problems to automate processing or to improve existing computer systems.
• Confer with personnel of organizational units involved to analyze current operational procedures, identify problems, and learn specific input and output requirements.
• Write detailed descriptions of user needs, program functions, and steps required to develop or modify computer programs.
• Review computer system capabilities, specifications, and scheduling limitations to determine if requested program or program change is possible within existing system.
• Design, develop, and optimize scalable data solutions on Databricks, leveraging PySpark or Scala for large-scale data processing.
• Build and maintain ingestion pipelines, Declarative Pipelines (DLT), and Medallion Architecture (Bronze, Silver, Gold) to support enterprise analytics and reporting.