Lead end-to-end delivery of scalable, reliable, and high-quality data products.
Design and implement data ingestion, cleansing, and transformation pipelines from diverse source systems into a cloud data lake
Support advanced analytics, data warehousing, and data science initiatives
Develop and present Conceptual, Logical, and Physical Data Models based on business requirements
Architect and implement complex cloud-based data engineering solutions on AWS and/or GCP
Collaborate closely with business stakeholders, analysts, and technical teams across multiple locations
Mentor, coach, and support the continuous development of data engineers within the team
Contribute to hiring, onboarding, and growing a high-performing data engineering team
Drive best practices, innovation, and continuous improvement across the data engineering function

Requirements

8+ Years of experience
Strong SQL expertise with experience across multiple source systems (including Microsoft SQL Server)
Hands-on experience with Snowflake cloud data warehouse
Experience using dbt for data transformation, testing, deployment, and monitoring
Strong understanding of data modeling for structured and unstructured data
Solid experience in Cloud Data Engineering on AWS and/or GCP
Proficiency in Python or Java for data engineering and platform development
Experience working in Agile delivery teams with CI/CD, DevOps, and DataOps practices
AWS Experience (Required): Amazon S3, Managed Workflows for Apache Airflow (MWAA), AWS Glue, AWS Lambda, SNS & SQS, DynamoDB
Nice to Have: Experience with Tableau for building interactive dashboards and data visualizations
Infrastructure as Code (IaC) using Terraform (or equivalent tools)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

SQLSnowflakedbtdata modelingPythonJavaCloud Data EngineeringAgileCI/CDInfrastructure as Code

leadershipmentoringcollaborationcoachingcommunicationinnovationcontinuous improvement