GENNTE TechnologiesRemote
Decision Analytics Full Stack Sr. Data Engineer
United States of America
Full Time
3 hours ago
$140,000 - $150,000 USD
Visa Sponsor
Key skills
PythonSQLMLETLELTData EngineeringSnowflakeRedshiftKafkadbtAWSVaultS3IAMGlueAthenaKinesisSplunkGitCI/CDMentoring
About this role
GENNTE Technologies is seeking a Senior Data Engineer to lead the design and development of scalable data platforms. The role involves defining architectural roadmaps, mentoring teams, and collaborating with various stakeholders to deliver high-performance data solutions.
Responsibilities:
- Define and drive the architectural roadmap for scalable, secure, and high-performance data platforms
- Lead the design, development, and optimization of end-to-end data pipelines for batch and real-time processing
- Mentor engineering teams, conduct code reviews, establish best practices, and accelerate project delivery
- Collaborate with Data Scientists, ML Engineers, Analysts, and business stakeholders to build production-ready data solutions
- Develop and maintain data ingestion and transformation frameworks using tools such as dbt Core, AWS Glue, and Talend
- Build and manage workflow orchestration solutions using Dagster, Talend, or similar platforms
- Implement real-time data streaming solutions using AWS Kinesis, Confluent Kafka, or related technologies
- Drive DataOps and DevOps best practices, including CI/CD, monitoring, observability, and automated testing
- Optimize performance and cost across Snowflake, Amazon Redshift, AWS Athena, and Iceberg-based lakehouse environments
- Ensure data quality, governance, privacy, security, and regulatory compliance across the data ecosystem
Requirements:
- 15+ years of progressive experience in Data Engineering, Data Architecture, or related fields
- Strong expertise in AWS cloud services including S3, IAM, VPC, Glue, and related data services
- Hands-on experience with: Snowflake, Amazon Redshift, AWS Athena, dbt Core, Talend, Apache Iceberg, AWS Glue Catalog, Splunk, AWS Streaming Services (Kinesis, MSK, etc.), Git
- Advanced proficiency in: Python, PySpark, SQL
- Strong understanding of: Data Modeling (Dimensional, Data Vault), ETL/ELT Architecture, Metadata Management, Data Governance, DataOps & DevOps
- Proven experience building and supporting petabyte-scale cloud data platforms
- Insurance domain experience is a plus
- Open to candidates with strong experience in modern cloud-based data engineering and enterprise-scale data platforms