Data Engineer

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Nasstar

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💼 Consulting

📦 Logistics

Consulting • Logistics • Cloud Computing

Nasstar is a cloud service specialist that designs, implements, and manages multi-cloud solutions, innovative communication tools, and high-performance networking. With a strong global presence, Nasstar supports customers across various industries by offering a comprehensive suite of cloud services. The company has undergone several strategic acquisitions and rebranding efforts to enhance its capabilities, such as the acquisitions of Modality, Outsourcery, and others. Nasstar is committed to evolving with the rapidly changing tech industry and values enthusiastic individuals who are driven and passionate about making a difference.

📋 Description

• Design, develop and maintain scalable ETL/ELT pipelines using dbt, Snowflake and/or Databricks. • Build and optimise cloud-native data lake solutions using Amazon S3. • Develop production-grade data pipelines using AWS services including Glue, Lambda, Step Functions or MWAA. • Build scalable data models that support analytics and business reporting. • Optimise SQL transformations and data processing for performance and cost efficiency. • Develop dashboards and reporting solutions using Databricks Dashboards, Snowsight or Amazon QuickSight. • Collaborate with architects, engineers and client stakeholders to deliver high-quality production solutions. • Follow software engineering best practices including version control, testing and CI/CD.

🎯 Requirements

• 3+ years' commercial experience as a Data Engineer delivering production data solutions. • Strong hands-on experience with dbt is essential. • Strong SQL skills. • Strong Python programming experience. • Commercial experience using Snowflake or Databricks as enterprise data platforms. • Experience building and maintaining modern ETL/ELT pipelines. • Experience working within AWS cloud environments. • Experience building cloud-native data lake solutions using Amazon S3. • Experience using AWS-native orchestration and ingestion services such as AWS Glue, AWS Lambda, AWS Step Functions, or MWAA (Apache Airflow). • Experience designing and optimising data pipelines for performance, scalability and reliability. • Experience developing dashboards or reporting solutions using Databricks Dashboards, Snowsight or Amazon QuickSight. • Good understanding of data modelling principles. • Familiarity with Git and CI/CD practices. • Excellent communication skills with the ability to work collaboratively within technical teams and with client stakeholders.

🏖️ Benefits

• Fully remote working. • Work on exciting enterprise-scale projects across multiple industries. • Modern Azure and Databricks technology stack. • Access to AWS, Microsoft and Databricks certifications. • Work alongside highly experienced architects and engineers. • Clear career progression into Senior Data Engineer and beyond. • Collaborative engineering culture focused on technical excellence. • Competitive salary and benefits.