Senior Data Engineer

Tango is a leader in cloud-based Software-as-a-Service solutions for managing end-to-end real estate and facilities lifecycles, serving hundreds of customers across more than 140 countries. The Senior Data Engineer will join the Data Engineering team to own scalable data pipelines, dbt transformation layers, production databases, and data warehouses. The role also focuses on data quality and governance, observability, and cross-functional collaboration with application engineering, Product, and Data Analytics teams.

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.)

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 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)