Note: The job is a remote job and is open to candidates in USA. Tango is a cloud-based Software-as-a-Service company providing solutions to manage end-to-end real estate and facilities lifecycles. The Senior Data Engineer will join the Data & AI Engineering team to design, maintain, and optimize scalable data pipelines, databases, and warehouses while ensuring data quality and governance. The role also involves collaborating with application engineering, Product, and Data Analytics teams to support APIs, curated datasets, observability, and production troubleshooting.
Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines using AWS-native services (Glue, Lambda, Step Functions, S3)
- Develop automated workflows to ingest, transform, and validate large volumes of structured and semi-structured data
- Monitor pipeline performance, reliability, and cost efficiency; implement proactive improvements
- Own the transformation layer in dbt: models, tests, sources, and documentation. Every dataset that reaches the warehouse is modeled in dbt and validated against source
- Manage and optimize production databases (Postgres, TimescaleDB) and our OLAP data warehouse (Redshift, etc)
- Implement database performance tuning, indexing strategies, query optimizations, and schema evolution best practices
- Oversee data retention, partitioning, and backup/restore strategies
- Build automated data validation frameworks and anomaly detection, anchored in dbt tests and source-reconciliation checks
- Establish and enforce data quality SLAs across ingestion and reporting layers
- Maintain metadata, lineage, and documentation standards to support auditability (SOC 1/2, ISO)
- Work with application engineering teams to design 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 using monitoring and alerting tools (CloudWatch, Datadog, etc.)
Skills
- *Applicants must be authorized to work in the U.S. for any employer
- 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 data services (Glue, Lambda, Step Functions, S3, Redshift, RDS/Postgres)
- Hands-on experience with ETL/ELT pipeline design, orchestration, and performance tuning
- Strong experience with production databases (Postgres, TimescaleDB, etc.)
- Solid understanding of data modeling (OLTP, OLAP/star schema), warehousing, and analytics workloads
- Experience with data quality frameworks, validation, and monitoring
- Production experience with dbt : building and testing models, managing sources and lineage, structuring a project across staging/intermediate/mart layers and running it in CI
- Experience with Git-based workflows and CI/CD for data: pull requests, code review and automated testing of transformations
- Experience with time-series data and high-volume ingestion pipelines
- Background in the Energy, Sustainability, or IoT data domain
- Dbt Semantic Layer or comparable metrics-layer experience (Cube, LookML , Omni semantic models)
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- 401(k) plan with company match
- Generous paid time off
- Fully remote work arrangement
- Flexible work arrangements that promote productivity and balance
- Inclusive and collaborative workplace culture
Company Overview