Senior Data Engineer

This is a fully remote position, open to applicants in United States, +1 more state.

📋 Description

• Design, create, and sustain scalable ETL/ELT pipelines utilizing AWS-native services.

• Develop automated workflows for the ingestion, transformation, and validation of structured and semi-structured data.

• Monitor the performance, reliability, and cost-effectiveness of pipelines and implement enhancements.

• Oversee the dbt transformation layer, which includes models, tests, sources, and documentation.

• Manage and optimize production Postgres and TimescaleDB databases, along with the Redshift OLAP warehouse.

• Execute performance tuning, indexing, query optimization, schema evolution, retention, partitioning, and backup/restore strategies.

• Create automated frameworks for data validation and anomaly detection.

• Establish and uphold data quality SLAs.

• Maintain standards for metadata, lineage, and documentation to ensure auditability.

• Collaborate with application engineering on APIs, microservices, and data contracts.

• Support Product and Data Analytics teams by providing curated datasets and high-performance query patterns.

• Troubleshoot production issues and enhance observability using monitoring and alerting tools.

⛳️ Requirements

• A minimum of 5 years of professional experience as a Data Engineer or in a similar capacity.

• Strong proficiency in Python, SQL, and contemporary data engineering frameworks.

• Extensive experience with AWS Glue, Lambda, Step Functions, S3, Redshift, and RDS/Postgres.

• Practical experience in designing, orchestrating, and performance-tuning ETL/ELT pipelines.

• Significant experience with production databases, specifically Postgres and TimescaleDB.

• Knowledge of OLTP, OLAP/star-schema data modeling, warehousing, and analytics workloads.

• Familiarity with data quality frameworks, validation processes, and monitoring techniques.

• Hands-on experience with dbt, covering models, tests, sources, lineage, layered project structures, and CI execution.

• Experience with Git-based workflows and CI/CD for data, including pull requests, code reviews, and automated transformation testing.

• Preferred experience with time-series data and high-volume ingestion pipelines.

• A background in Energy, Sustainability, or IoT data is preferred.

• Familiarity with the dbt Semantic Layer or similar metrics-layer tools is preferred.

• Must possess authorization to work in the U.S. for any employer.

• Must not require employment-based visa sponsorship.

🏝️ Benefits

• Health, dental, and vision insurance.

• 401(k) plan with company matching.

• Generous paid time off.

• Fully remote work environment.

• Inclusive and collaborative culture.

• Equal opportunity employment.