Data Engineering Leadership Opportunity
1 day ago
Company Overview
At Wenger & Watson Inc., we are committed to delivering cutting-edge solutions that drive business growth and success. Our team is dedicated to creating a collaborative and innovative environment where talented professionals can thrive.
Job Description
We are seeking an experienced Data Engineering Manager to lead our data engineering team in developing and maintaining our data platform. The ideal candidate will have a strong background in AWS-based data engineering, including orchestrating and governing data pipelines, integration, data modeling, and release management.
Key responsibilities include:
■ Designing, building, and maintaining batch or real-time data pipelines in production.
■ Developing ETL/ELT data pipeline processes to extract, transform, and load data from multiple sources.
■ Automating data workflows such as data ingestion, aggregation, and ETL processing using various techniques and tools.
■ Ensuring data accuracy, integrity, privacy, security, and compliance through quality control procedures.
Required Skills and Qualifications
To be successful in this role, you will need:
■ A minimum of 12-15 years of experience in data engineering, with a strong focus on AWS-based solutions.
■ Extensive experience in leading DevOps sprint teams using Scrum, translating business requirements into deliverable user stories, and coordinating development activity.
■ Hands-on experience with AWS tools and services (e.g., S3, EC2, Athena, Redshift, Glue, EMR, Lambda, RDS, Kinesis, DynamoDB, QuickSight).
■ Strong experience in workflow management and orchestration tools (e.g., Airflow).
■ Familiarity with CI/CD technologies (e.g., Git, Jenkins, Spinnaker, Ansible).
Salary and Benefits
We offer a competitive salary range of $150,000 - $200,000 per annum, depending on experience. In addition to a comprehensive benefits package, you will also receive opportunities for professional growth and development in a dynamic and innovative environment.
How to Apply
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