Senior Data Engineer

*Applicants must be authorized to work in the U.S. for any employer.

*We cannot sponsor employment-based visas at this time.

About The Company: 

With hundreds of customers across more than 140 countries, Tango is the leader in cloud-based Software-as-a-Service (SaaS) solutions use to manage the end-to-end real estate and facilities lifecycles. Tango’s Store Lifecycle Management and Integrated Workplace Management System software, deliver a single solution spanning real estate, design & construction, lease administration & accounting, facilities maintenance, occupancy management, energy & sustainability, desk booking, visitor and space management.  

We are looking for a Senior Data Engineer to join our dynamic and growing Data Engineering team.

Key Responsibilities: 

Data Pipeline Ownership

• 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. 

Database & Warehouse Management 

• 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. 

Data Quality & Governance 

• 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). 

Cross-Functional Collaboration 

• 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.). 

Required Skills: 

• 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. 

Preferred