Sr. Data engineer [Remote]

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Sr. Data Engineer in the United States.

This role is focused on modernizing and scaling enterprise data infrastructure by transforming legacy on-premise systems into a cloud-native analytics platform. You will play a key part in migrating traditional SQL Server and SSIS-based pipelines into Google Cloud Platform, enabling more scalable, efficient, and reliable data workflows. The position is highly hands-on and centers on building robust ETL/ELT pipelines, optimizing data models, and ensuring high-quality data delivery for business intelligence use cases. You will work closely with analytics and BI teams to support Tableau-driven reporting and decision-making across the organization. The environment is collaborative and transformation-driven, requiring strong engineering ownership and a passion for cloud modernization. This is a high-impact role where your work directly shapes the future of enterprise data architecture and analytics performance.

Accountabilities:

• Lead the migration of SSIS-based ETL pipelines to cloud-native workflows using DBT and GCP tools (Dataflow, Dataform, Cloud Composer)
• Design, build, and optimize scalable data models in BigQuery following dimensional modeling best practices
• Maintain and enhance SQL-based transformations to ensure performance, accuracy, and reliability in cloud environments
• Collaborate with BI teams to align data marts with Tableau reporting and analytics requirements
• Ensure data quality, lineage, integrity, and observability through testing, documentation, and monitoring practices
• Support the decommissioning of legacy on-prem systems and design hybrid transitional architectures where needed
• Establish engineering best practices and mentor junior data engineers in cloud data development patterns
• Partner with cross-functional teams to support secure, efficient, and well-governed data pipelines

Requirements

• 5+ years of experience in data engineering with strong SQL and ETL development skills
• Hands-on experience with SSIS and SQL Server–based data warehouse environments
• Strong proficiency in Google BigQuery or similar cloud data warehouses
• Experience with DBT or other modern data transformation frameworks
• Solid understanding of dimensional modeling and data warehousing principles
• Proven experience migrating on-prem data pipelines to cloud platforms
• Familiarity with GCP services such as Cloud Storage, Dataflow, Pub/Sub, Composer, and IAM
• Experience supporting BI tools such as Tableau is highly preferred
• Familiarity with Git-based CI/CD practices for data pipelines
• Exposure to infrastructure-as-code tools like Terraform is a plus
• Strong problem-solving mindset with a focus on automation, scalability, and data reliability
• Excellent collaboration skills and ability to work across BI, analytics, and engineering teams

Benefits

• Competitive salary aligned with experience and expertise
• Fully remote work across the United States
• Opportunity to lead cloud modernization and data platform transformation initiatives
• Exposure to modern data stack technologies (GCP, DBT, BigQuery)
• Collaborative, engineering-driven work environment
• Professional development and learning opportunities in cloud and data engineering
• Opportunity to work on high-impact enterprise analytics systems
• Strong focus on engineering best practices and scalable architecture design

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.