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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:
Competitive Compensation We recognize and reward your contributions with a salary package that reflects your value.
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.
Flexible Work Environment Whether remote, hybrid, or in-office, we support work arrangements that promote productivity and balance.
Inclusive & Collaborative Culture We foster a workplace where diverse perspectives are valued, teamwork is encouraged, and everyone has a voice.
Tango is proud to be an equal opportunity employer. We are committed to equal opportunity regardless of race, ethnicity, religion, parental status, sexual orientation, age, citizenship, disability, or veteran status.