Senior Data Engineer
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Job Description
Senior Data Engineer building AWS and dbt data pipelines for Tango’s cloud real-estate and facilities SaaS platform. Managing databases, warehouses, data quality, and analytics-ready datasets.
Responsibilities:
- Design, build, and maintain scalable ETL/ELT pipelines using AWS-native services
- Develop automated workflows to ingest, transform, and validate structured and semi-structured data
- Monitor pipeline performance, reliability, and cost efficiency and implement improvements
- Own the dbt transformation layer, including models, tests, sources, and documentation
- Manage and optimize production Postgres and TimescaleDB databases and the Redshift OLAP warehouse
- Implement performance tuning, indexing, query optimization, schema evolution, retention, partitioning, and backup/restore strategies
- Build automated data validation and anomaly-detection frameworks
- Establish and enforce data quality SLAs
- Maintain metadata, lineage, and documentation standards for auditability
- Collaborate with application engineering on APIs, microservices, and data contracts
- Support Product and Data Analytics teams with curated datasets and high-performance query patterns
- Troubleshoot production issues and improve observability with monitoring and alerting tools
Requirements:
- 5+ years of professional experience as a Data Engineer or similar role
- Strong expertise with Python and SQL and modern data engineering frameworks
- Deep experience with AWS Glue, Lambda, Step Functions, S3, Redshift, and RDS/Postgres
- Hands-on experience designing, orchestrating, and performance-tuning ETL/ELT pipelines
- Strong experience with production databases, including Postgres and TimescaleDB
- Understanding of OLTP, OLAP/star-schema data modeling, warehousing, and analytics workloads
- Experience with data quality frameworks, validation, and monitoring
- Production experience with dbt, including models, tests, sources, lineage, layered project structure, and CI execution
- Experience with Git-based workflows and CI/CD for data, including pull requests, code review, and automated transformation testing
- 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 comparable metrics-layer tools preferred
- Must be authorized 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 match
- Generous paid time off
- Fully remote work environment
- Inclusive and collaborative culture
- Equal opportunity employment
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