Key skills
AWS data servicesPythonSQLETL/ELT pipeline designProduction databasesData modelingData quality frameworksMonitoring toolsTime-series dataEnergy domain experienceCross-functional collaborationRETLELTData EngineeringAnalyticsRedshiftAWSLambdaS3RDSCloudWatchGluePostgresTimescaleDBDatadog
About this role
Tango is dedicated to helping businesses make smarter decisions through technology and data. They are seeking a Senior Data Engineer to join their R&D team, responsible for designing and maintaining ETL/ELT pipelines, managing databases, ensuring data quality, and collaborating with cross-functional 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
- 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
- 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
- Experience with time-series data and high-volume ingestion pipelines
- Background in the Energy, Sustainability, or IoT data domain