Solution Engineer, Data Engineering - Manager

Develop and maintain cloud-native data pipelines for batch and streaming ingestion Develop transformation and modeling patterns enabling analytics and AI/ML use cases Build and operate orchestration workflows with versioning, testing, promotion, rollback, and runbooks Embed data quality, lineage, and observability into pipelines and datasets Implement secure data access patterns aligned to enterprise and regulatory requirements Optimize performance and cost across compute and storage Collaborate with scientists, analysts, data scientists, and engineers to translate requirements into production solutions Contribute to reusable standards, templates, documentation, examples, and onboarding materials Stay current with technologies and best practices; support skill development and knowledge sharing Pair with domain teams to define datasets and data products Review pull requests and improve data quality checks and observability dashboards Troubleshoot production issues, maintain runbooks, and perform root-cause follow-up Ship changes through

CI/CD

and document delivered solutions Report to the Principal Engineer, Data Engineering Requirements Bachelor's degree in a relevant field (e.g., Computer Science, Data Science, Data Engineering, Bioinformatics, Engineering, or related discipline) 4+ years of experience in data engineering, software engineering, or closely related roles Strong proficiency in Python and SQL for data processing, automation, and testing Hands-on experience with cloud platforms (AWS, GCP, Azure) and cloud-native storage/compute services Experience with one or more modern data processing or lakehouse/warehouse technologies (e.g., Spark, Databricks, Snowflake, Redshift, Delta Lake, Iceberg) Experience with workflow orchestration and scheduling (e.g., Airflow) and CI/CD using Git-based workflows Strong understanding of data modeling, data integration patterns, and software engineering best practices (code review, testing, documentation) Working knowledge of security best practices for data platforms (IAM, secrets management, encryption, least privilege) and operating in regulated environments Strong problem-solving skills and eagerness to learn in a collaborative environment Fluent in English; capable of clear technical communication across scientific and engineering disciplines Candidates must be authorized to be employed in the U.S. by any employer U.S. work visa sponsorship is not available for this role now or in the future This position requires permanent work authorization in the United States Core Competencies Demonstrates expertise in developing and maintaining cloud-native data pipelines, with strong proficiency in Python and SQL for data processing. Capable of implementing secure data access patterns and optimizing performance across cloud platforms while collaborating effectively with cross-functional teams. Highest-signal resume keywords Cloud-Native Data Pipeline Development Python Proficiency SQL Proficiency Workflow Orchestration (Airflow) Data Modeling and Integration ATS Optimization Keywords Hard Skills Data Engineering Software Engineering Data Processing Automation Testing Data Integration Patterns CI/CD Data Quality Checks Observability Root-Cause Analysis Soft Skills Problem-Solving Collaboration Technical Communication Eagerness to Learn Industry Keywords Data Quality Data Lineage Observability Security Best Practices Regulated Environments Tools & Technologies AWS GCP Azure Spark Databricks Snowflake Redshift Delta Lake Iceberg Git #J-18808-Ljbffr Jobtailor