Senior Data Engineer & Data Strategy Leader

Torq; Dallas (TX); Hybrid; USD 130,000 - 170,000; Full time

Benefits offered by this job

Competitive Salary

Unlimited PTO

Best-in-class health/vision/dental

401K options

Parental Leave

Career growth & mobility

Diverse project opportunities

Job summary

Torq is seeking data engineers and technical leaders to design systems that solve real business challenges and influence strategic decisions for clients. You will guide clients through the full data lifecycle—from raw ingestion to advanced analytics—and help unlock the full potential of their data ecosystem.

As part of a collaborative team, you’ll build scalable data pipelines, define KPIs, and promote best practices across real-time and batch analytics.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Information Systems, Engineering, or a related field
• 8+ years of hands-on data warehousing, ETL development, and data modeling (conceptual and physical) or related work
• Willingness to work a hybrid schedule (2-3 days per-week onsite)
• Data acquisition & sourcing: APIs, flat files, event streams
• Solid experience with ETL/ELT pipeline development, scripting automation, including performance optimization & data quality assurance
• Tools like: Python, SQL, Apache Airflow, dbt, Kafka, Terraform, etc.
• Cloud data platforms: Azure Data Services (preferred), AWS, or Google Cloud Platform
• Data Warehousing: Synapse, Snowflake, BigQuery, Redshift, etc.
• Proficient in Reporting Platforms to query large data sets (PowerBI, Tableau, Looker)
• Familiarity with data governance security, and compliance best practices (Collibra, Unity Catalog, Purview)
• Strong Snowflake and Python data engineering experience with hands-on pipeline development
• Proficient in SQL and experienced in designing efficient queries for large-scale data sets
• Strong communication skills and the ability to collaborate with both technical and non-technical stakeholders

Responsibilities

• Build strong relationships with data consumers to understand usage patterns and design scalable data models
• Design, develop, and deliver high-quality data pipelines that align with privacy, governance, and performance best practices
• Build real-time and batch data integrations from various source systems into cloud-based data lakes and warehouses
• Develop and maintain ETL/ELT processes for streaming and offline analytics
• Define and implement KPIs to measure efficiency, quality, and reliability of data engineering processes
• Participate in code reviews, promote clean, maintainable code aligned with engineering best practices
• Create and maintain data definitions and metadata consistent with data management standards
• Provide operational support for data integration and transformation workflows in production

Skills

8+ years data warehousing/ETL

Python

SQL

Airflow

dbt

Kafka

Terraform

PowerBI/Tableau/Looker

Education

Bachelor’s degree in Data Science/CS/IS/Engineering

Tools

Azure Data Services

AWS

GCP

Snowflake

BigQuery

Redshift

Synapse

Databricks

PowerBI

Tableau

Looker

Collibra

Unity Catalog

Purview

GitHub Actions

Azure DevOps

Jenkins

Job description

Torq is seeking data engineers and technical leaders to design systems that solve real business challenges and influence strategic decisions for clients. You will guide clients through the full data lifecycle—from raw ingestion to advanced analytics—and help unlock the full potential of their data ecosystem.

As part of a collaborative team, you’ll build scalable data pipelines, define KPIs, and promote best practices across real-time and batch analytics.