Job Opportunities API

Are you driven by the challenge of turning complex data into actionable insights? Do you thrive on building scalable data systems that power better decisions and real business impact? If you’re ready to lead with purpose and bring data to life, Torq is the place for you. We are looking for data engineers and technical leaders who don’t just build pipelines and create dashboards—they design systems that solve real business challenges and influence key strategic decisions for our clients. At Torq, you’ll join a collaborative team that takes on complex, high-impact projects. You’ll guide clients through the full data lifecycle—from raw ingestion to advanced analytics—and help them unlock the full potential of their data ecosystem. What You Could Be Doing  While every project we work on is different, below is a high-level overview of some of the responsibilities/hats you may wear:  Build strong relationships with data consumers to understand usage patterns and design intuitive, scalable data models. Design, develop, and deliver high-quality data pipelines that align with privacy, governance, and performance best practices. Build both real-time and batch data integrations from a variety of source systems into cloud-based data lakes and warehouses. Develop and maintain ETL/ELT processes and tools to support both streaming and offline analytics. Define and implement key performance indicators (KPIs) to measure the efficiency, quality, and reliability of data engineering processes. Participate in code reviews, promoting clean, maintainable, and well-documented 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 environments. What You Bring to the Table  When you join our team, you’re a consultant first. This means there are core skills we expect out of each of our team members. These include:  Bachelor’s degree in Data Science, Computer Science, Information Systems, Engineering, or a related field 5+ years of hands-on experience in data warehousing, ETL development, and data modeling (both conceptual and physical) or other related technical & analytical 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. Strong understanding of data architecture, schema design, normalization/denormalization, and data lifecycle management  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 Ex: PowerBI, Tableau, Looker, or similar tools Familiarity with data governance security, and compliance best practices (Collibra, Unity Catalog, Purview) 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 In addition, each one of our consultants brings a unique and valuable toolbox of skills with them specific to their practice. Below are some examples of skills we are always looking to add to the team (don’t worry – we don’t expect you to have all of them, but they are always a plus!):  Experience with CI/CD pipelines for data solutions using tools like GitHub Actions, Azure DevOps, or Jenkins Exposure to Power BI or other BI tools for data visualization and reporting Experience with Delta Lake, Data Mesh, or Lakehouse architectu