Trinetix
Tech / AI / Software
SQLSenior/DataEngineer(L2)
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optimal for Senior candidates.
“SQL Senior / Data Engineer (L2) at Trinetix. Skills: SQL, Data Engineering, Cloud Data Platforms, ETL/ELT Pipelines, Power BI Reporting. Own the data and analytics support queue: pipeline failures, ETL/ELT errors, Power BI dashboard issues. Monitor and remediate data pipelines across Azure and AWS environments”
Industry & Context.
Troubleshooting; Remediation; Performance troubleshooting; Job failure diagnosis; Diagnostic queries
On-call rotation — data incidents, Covers P1/P2 data pipeline and platform failures outside business hours, Shared rotation between Ukraine and Argentina Data Engineers — approximately every other week per person, Activation expected when a critical pipeline failure impacts business operations or reporting delivery, Response expected within 1 hour of activation, On-call compensation applies per company policy
What They're Looking For.
Must Have
Minimum 5 years of relevant experience, Azure: Data Factory, Azure SQL, Synapse Analytics — 5+ years required, AWS: S3, RDS, Glue — data pipeline and infrastructure support, Snowflake: Query writing, data loading, performance troubleshooting, Snowpipe, Databricks: Notebook execution, cluster management, job failure diagnosis, Delta Lake basics, Power BI: Dashboard connectivity, data source troubleshooting, refresh failures, DAX basics, SQL: Advanced — complex queries, stored procedures, performance tuning across SQL Server and cloud DBs, Pipeline tools: Apache Airflow or Azure Data Factory — DAG/pipeline monitoring and repair, Python: Scripting for data transformation, automation, and diagnostic tasks, Version control: GitLab — CI/CD pipeline basics for data workflows, 5+ years in data engineering or data platform support, Hands-on experience with at least 3 of: Azure, AWS, Snowflake, Databricks, English — required (all tickets, escalations, client communication)
Nice to Have
Production pipeline support experience strongly preferred
What You'll Do.
Own the data and analytics support queue: pipeline failures
Power BI dashboard issues
Monitor and remediate data pipelines across Azure and AWS environments
Write and execute SQL scripts for data fixes
and diagnostic queries
Support Snowflake and Databricks: query optimization
job failure diagnosis
Maintain CI/CD pipelines supporting data operations (Tier 1 monitoring
Handle SQL-heavy overflow tickets from the application support queues (HUB-Report
Coordinate with client data team on schema changes
and capacity planning
Perform minor data platform enhancements as assigned (up to 80 engineering hours)
Support vehicle telematics data infrastructure and related ingestion pipelines
How You'll Work.
Team & Collaboration
Coordinate with client data team on schema changes, pipeline updates, and capacity planning
Communication Scope
English — required (all tickets, escalations, client communication)
Full Job Description
### **Hybrid or full remote Full time ** Role Overview The SQL Senior / Data Engineer owns the data and analytics support queue — responsible for monitoring, troubleshooting, and remediating failures across cloud data platforms, ETL/ELT pipelines, and Power BI reporting. The role also handles SQL-level data fixes and record corrections that overflow from the application support queues. Minimum 5 years of relevant experience is required per contractual staffing requirements. ### Responsibilities · Own the data and analytics support queue: pipeline failures, ETL/ELT errors, Power BI dashboard issues · Monitor and remediate data pipelines across Azure and AWS environments · Write and execute SQL scripts for data fixes, record corrections, and diagnostic queries · Support Snowflake and Databricks: query optimization, job failure diagnosis, cluster management · Maintain CI/CD pipelines supporting data operations (Tier 1 monitoring, Tier 2 remediation) · Handle SQL-heavy overflow tickets from the application support queues (HUB-Report, data corrections) · Coordinate with client data team on schema changes, pipeline updates, and capacity planning · Perform minor data platform enhancements as assigned (up to 80 engineering hours) · Support vehicle telematics data infrastructure and related ingestion pipelines ### Required Technical Skills · **Azure:** Data Factory, Azure SQL, Synapse Analytics — 5+ years required per contractual staffing requirements · **AWS:** S3, RDS, Glue — data pipeline and infrastructure support · **Snowflake:** Query writing, data loading, performance troubleshooting, Snowpipe · **Databricks:** Notebook execution, cluster management, job failure diagnosis, Delta Lake basics · **Power BI:** Dashboard connectivity, data source troubleshooting, refresh failures, DAX basics · **SQL:** Advanced — complex queries, stored procedures, performance tuning across SQL Server and cloud DBs · **Pipeline tools:** Apache Airflow or Azure Data Factory — DAG/pipeline m
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