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Revecore · 4 hours ago

Senior Data Engineer

United States

Full-time

Remote

Senior Level

5+ years exp

Revecore is an innovative, technology-driven company that is committed to helping our clients, employees, and communities thrive. The Senior Data Engineer will join the Technology function, solving complex data problems for the Revecore Data Platform and will be responsible for building a modern data lakehouse platform that will transform Revecore and its capabilities.

AnalyticsManagement ConsultingMedical

Responsibilities

Own the implementation and quality of the data platforms, ensuring availability, reliability, resilience, and security while upholding consistent standards of engineering excellence

Continuously improve both the engineering practice and the quality of the domain's data outputs

Design and develop scalable, maintainable, and reliable data pipelines to support business and analytics needs

Collaborate with other Data Engineers to understand requirements and build tooling and automation that enhance developer efficiency

Monitor data systems and performance, identifying opportunities to optimize warehouse and infrastructure costs

Stay current with industry trends and emerging technologies across the data platform ecosystem to drive innovation and modernization

Qualification

PythonSQLData pipelinesKubernetesDockerSnowflakeAWSAzureTerraformCI/CDData modelingReal-time data technologiesDocumentation

Required

5+ years of experience designing and deploying data engineering solutions using Python, SQL, and modern orchestration/transformation frameworks (e.g., dbt, Airflow, Dagster, Prefect)

Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience)

Experience designing, building, and maintaining scalable, reliable data pipelines with containerized deployments on Kubernetes or Docker

Experience with modern data warehouses such as Snowflake, Redshift, or BigQuery

Proven ability to develop and support multi-cloud data platforms on Azure and AWS, including data lakes (ADLS, S3) and data warehouses (Synapse, Snowflake, Redshift); automate infrastructure using Terraform or CloudFormation

Expertise in pipeline optimization for performance, cost efficiency, and reliability using monitoring (Prometheus, Grafana), CI/CD (GitHub Actions, Jenkins), and data quality frameworks

Strong understanding of infrastructure as code, SDLC, and deployment automation

Proven ability to write clear documentation and promote best practices via knowledge sharing, code reviews, and technical guidance