About the job
Work Arrangement and Location
This is a full-time position based in Buenos Aires, Argentina. Flexible work options are available: choose hybrid or fully remote arrangements to fit your needs.
Role Overview
Trinetix is looking for a Senior SQL Data Engineer with strong Power BI skills. The role centers on managing the data and analytics support queue, with responsibility for monitoring, troubleshooting, and resolving issues across cloud data platforms, ETL/ELT pipelines, and Power BI reporting. The position also involves handling SQL-level data fixes and record corrections that come from application support queues. At least 5 years of relevant experience is required for this role, as specified by contractual staffing requirements.
What You Will Do
- Manage the data and analytics support queue, addressing pipeline failures, ETL/ELT errors, and Power BI dashboard issues
- Oversee and correct data pipelines in Azure and AWS environments
- Develop and run SQL scripts for data corrections, record adjustments, and diagnostic queries
- Support Snowflake and Databricks, including query optimization, job failure analysis, and cluster management
- Maintain CI/CD pipelines to support data operations, including Tier 1 monitoring and Tier 2 remediation
- Handle SQL-intensive overflow tickets from application support queues, such as HUB-Report and data corrections
- Work with client data teams on schema changes, pipeline improvements, and capacity planning
- Implement minor enhancements to data platforms (projects up to 80 engineering hours)
- Support vehicle telematics data infrastructure and related ingestion pipelines
Required Technical Skills
- Azure: Proficiency with Data Factory, Azure SQL, and Synapse Analytics (minimum 5 years required)
- AWS: Experience with S3, RDS, and Glue for data pipeline and infrastructure support
- Snowflake: Ability to write queries, load data, troubleshoot performance, and use Snowpipe
- Databricks: Skilled in executing notebooks, managing clusters, diagnosing job failures, and understanding Delta Lake basics
- Power BI: Expertise in dashboard connectivity, troubleshooting data sources, resolving refresh failures, and basic DAX
- SQL: Advanced knowledge for complex queries, stored procedures, and performance tuning across SQL Server and cloud databases
- Pipeline Tools: Familiarity with Apache Airflow or Azure Data Factory for monitoring and repairing DAGs/pipelines
- Python: Proficient in scripting for data transformation, automation, and diagnostics

