Senior Data Engineer

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

📋 Description

• Design, develop, and maintain scalable ETL/ELT pipelines utilizing AWS-native services.

• Create automated workflows to ingest, transform, and validate both structured and semi-structured data.

• Oversee pipeline performance, reliability, and cost-effectiveness, implementing enhancements as needed.

• Take ownership of the dbt transformation layer, including models, tests, sources, and documentation.

• Manage and optimize production databases, including Postgres and TimescaleDB, as well as the Redshift OLAP warehouse.

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

• Develop automated frameworks for data validation and anomaly detection.

• Establish and uphold data quality SLAs throughout the ingestion and reporting layers.

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

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

• Provide support to Product and Data Analytics teams with curated datasets and high-performance query patterns.

• Resolve production issues and enhance observability through 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 services, including Glue, Lambda, Step Functions, S3, Redshift, and RDS/Postgres.

• Hands-on experience in designing, orchestrating, and optimizing ETL/ELT pipelines.

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

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

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

• Production experience with dbt, covering models, tests, sources, lineage, staging/intermediate/mart layers, and CI execution.

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

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

• Employment-based visa sponsorship is not available.

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

• Preferred: background in Energy, Sustainability, or IoT data.

• Preferred: experience with dbt Semantic Layer or a comparable metrics-layer.

🏝️ Benefits

• Competitive compensation.

• Health insurance.

• Dental insurance.

• Vision insurance.

• 401(k) plan with company match.

• Generous paid time off.

• Fully remote work environment.

• Inclusive and collaborative culture.