Data Engineer \ DataBricks

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

Job Title: Data Engineer \ DataBricks

Location(s): Austin, TX
(Hybrid)

Role Summary
The Enterprise Data Engineer will design, build, and operate scalable data pipelines within an Azure environment in a Databricks Lakehouse architecture, with a primary focus on delivering and sustaining a software-driven data model for analytics and data consumption. This role is hands-on and execution-focused, supporting the project by engineering reliable ingestion from a diverse set of data producers, transformation, data quality checks, and datasets integrated with ServiceNow (ITSM/ITSLM) and ApptioOne (ITFM).

• Build and maintain data models to support data use and consumption, data integration with key systems, semantic analytics, reporting, and executive dashboards.
• Develop scalable data ingestion and transformation pipelines using a combination of Azure PaaS, Databricks, Delta Lake, Python and Spark SQL.
• Engineer integrations for ServiceNow operational and SLA datasets and ApptioOne financial and cost allocation data.
• Implement data quality checks, validation rules, and monitoring for end-to-end pipeline reliability.
• Apply Unity Catalog governance controls, including data access, lineage, and schema enforcement, as defined by architectural standards.
• Optimize pipeline performance, storage layouts, and query efficiency within the Databricks Lakehouse.
• Support CI/CD pipelines and DevOps automation for data engineering workflows using Azure DevOps and GitHub Actions.
• Collaborate with architects, client stakeholders, Capgemini teams, and service providers to deliver agreed reporting and analytics outcomes.
• Troubleshoot production data issues and support operational stability of analytics and reporting solutions.
• Contribute to documentation, runbooks, and operational standards for Databricks data pipelines.

• 5+ years of experience in Data Engineering or Analytics Engineering roles.
• Hands-on experience with Databricks, Delta Lake, and Spark-based data pipelines.
• Strong understanding of Medallion Architecture, particularly Gold/Platinum layer implementation.
• Proficiency in Python, SQL, and Spark (PySpark or SQL).
• Experience integrating enterprise systems such as ServiceNow (SLA, incident, CMDB data).
• Experience working with financial or cost management data (e.g., ApptioOne or equivalent ITFM tools).
• Experience with data modeling methodologies and tools.
• Familiarity with Unity Catalog concepts for data governance and access control.
• Experience with Power BI or similar BI tools consuming curated Lakehouse datasets.
• Experience with Azure data platform services (e.g., ADLS Gen2, Azure-native orchestration, and integration patterns), Azure DevOps, and GitHub-based CI/CD pipelines.

• Experience supporting public sector data initiatives.
• Familiarity with ITIL 4 / ITIL 5 concepts and SLA-based reporting.
• Experience supporting financial systems, SLA analytics, operational KPIs, or cost transparency dashboards.
• Exposure to MLflow, Feature Store, or AI/ML enablement pipelines (implementation support rather than architecture ownership).

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.