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:
Required
- 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
- 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).
What We Offer
We’re committed to creating an environment where you can thrive—professionally and personally. Our offerings include:
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Competitive Compensation We recognize and reward your contributions with a salary package that reflects your value.
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Comprehensive Benefits Including health, dental, and vision insurance, a 401(k) plan with company match, and generous paid time off to support your well-being.
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Flexible Work Environ