AWS Data Engineer - Power BI

Responsibilities Design, develop, and maintain scalable data pipelines and ETL/ELT processes. Build and manage data solutions using native AWS services. Develop and maintain Power BI dashboards, reports, semantic models, and datasets. Integrate data from multiple sources into AWS-based data platforms. Implement CI/CD pipelines for data and analytics deployments. Automate infrastructure and data engineering processes. Monitor data pipelines, Power BI refreshes, and production environments. Troubleshoot pipeline failures, data quality issues, and deployment problems. Implement data validation, monitoring, logging, and alerting. Work with development, analytics, and business teams to understand requirements. Follow DevOps and DataOps best practices around version control, automation, testing, and release management. Support continuous improvement of data platforms and reporting solutions. Mandatory: Strong hands-on Power BI experience. Strong hands-on experience with native AWS services.

Experience in Data Engineering / DataOps. Experience building ETL/ELT data pipelines. Experience with data modelling and data warehousing. Experience with CI/CD and DevOps practices. Experience with Git and source-code management. Strong troubleshooting and problem-solving skills. AWS Experience Candidates should have practical experience with relevant AWS data services, such as: Amazon S3 AWS Glue Amazon Redshift AWS Lambda Amazon Athena Amazon RDS AWS IAM Amazon CloudWatch Experience with services such as Kinesis, EMR, Step Functions or MWAA/Airflow would be advantageous. AWS data engineering roles commonly use services such as S3, Glue, Redshift, Lambda, Kinesis and IAM for data platforms and pipelines. Power BI Experience Power BI Desktop and Power BI Service. Dashboard and report development. Data modelling and relationships. DAX and Power Query. Dataset and semantic model development. Power BI deployment and refresh management. Row-Level Security (RLS). Performance optimisation. Integration of Power BI with cloud/data platforms. DevOps / Automation Git/GitHub/GitLab. Infrastructure as Code such as Terraform or CloudFormation. Automated deployments across environments. Monitoring and logging. Release and configuration management. Production support and incident troubleshooting. Python or another scripting language. AWS certification. Terraform. Apache Airflow / MWAA. Databricks or Spark. Kafka/Kinesis. dbt. Experience working in Agile/Scrum environments. Experience 4+ years of experience in Data Engineering, DevOps, DataOps, or a closely related role. Proven experience delivering data solutions in AWS. Strong Power BI development and production support experience. Experience working with enterprise data platforms and cloud environments. Key Technologies AWS | Power BI | SQL | Python | S3 | Glue | Redshift | Lambda | Athena | IAM | CloudWatch | ETL/ELT | Data Modelling | CI/CD | Git | Terraform | DevOps/DataOps Mandatory requirement: Candidates must have both strong Power BI experience and hands-on native AWS experience. Diversity and Inclusion At Scrumconnect Consulting, we believe that diversity drives innovation. We are committed to creating an inclusive environment where every individual is respected, valued, and supported. We welcome applications from candidates of all backgrounds and experiences, and we actively encourage applications from women, people with disabilities, underrepresented communities, and those seeking flexible working arrangements. #J-18808-Ljbffr