Senior Data Engineer - AWS, dbt & Scalable ETL Pipelines

Locatee AG; United States; Hybrid; USD 125,000 - 165,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Flexible work environment

Inclusive culture

Job summary

Tango is seeking a Senior Data Engineer to join our Data & AI Engineering team. You will design, build, and maintain scalable ETL/ELT pipelines on AWS, owning the dbt transformation layer and ensuring data quality and governance across the data stack.

You will collaborate with application teams to design APIs, data contracts, and support analytics with curated datasets, while optimizing performance, cost, and observability. Flexible work arrangements are supported.

Qualifications

• 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.

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).

Skills

Python

SQL

AWS

ETL/ELT

dbt

Git/CD

PostgreSQL

TimescaleDB

Data Modeling

Data Quality

Tools

AWS Glue

AWS Lambda

AWS Step Functions

Amazon S3

Redshift

RDS/Postgres

Job description

Tango is seeking a Senior Data Engineer to join our Data & AI Engineering team. You will design, build, and maintain scalable ETL/ELT pipelines on AWS, owning the dbt transformation layer and ensuring data quality and governance across the data stack.

You will collaborate with application teams to design APIs, data contracts, and support analytics with curated datasets, while optimizing performance, cost, and observability. Flexible work arrangements are supported.