Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Sep 22, 2025. XTGlobal scores D on the Alion truth index.
Key
Responsibilities: Design, build, and maintain scalable data pipelines using Azure Data Factory for data ingestion, transformation, and orchestration. Develop and optimize big data solutions and advanced analytics workflows using Azure Databricks. Create, manage, and publish Power BI dashboards and reports to deliver actionable insights to business stakeholders. Collaborate with data architects, analysts, and business teams to gather requirements and translate them into technical solutions. Implement data modeling, data integration, and ETL/ELT processes within Azure cloud environments. Ensure data quality, security, governance, and compliance in all data management activities. Monitor, troubleshoot, and optimize performance of data pipelines, analytics processes, and BI solutions. Support ad-hoc data requests, business analysis, and reporting needs.
Requirements
Requirements Proven experience working with Microsoft Azure ecosystem (Data Factory, Databricks, Power BI). Strong background in data engineering, ETL processes, and big data solutions. Hands-on experience in SQL, Python, or Scala for data transformation and analytics. Strong understanding of data modeling, data warehousing, and data visualization principles. Ability to optimize queries, pipelines, and dashboards for performance and scalability. Excellent problem-solving and analytical skills. Strong communication and collaboration skills to work with cross-functional teams. Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
Preferred
Qualifications Microsoft certifications such as Azure Data Engineer Associate, Azure Solutions Architect, or Power BI certification. Experience with Azure Synapse Analytics, Azure SQL Database, or other Azure data services. Prior experience in data governance, MDM, or cloud security practices. Exposure to agile methodologies and DevOps practices for data pipelines.

