D-ploy is an IT and Engineering Solutions company with operations throughout the EMEA region including Switzerland, Germany, Czech Republic, Austria, UK, as well as the USA. We pride ourselves on delivering innovative and superior services and solutions to numerous industry-leading clients. By building relationships and trusted partnerships within the IT community, we optimize our customer‘s IT productivity and contribute to the organization’s success and value. We are interested in talking to engaging, flexible, and solution-oriented individuals who are looking to become a part of a dynamically growing and international organization. We are focused on creating value where IT counts, join us! Tasks and Responsibilities Lead and Support Databricks Implementations Design, architect, and implement scalable data solutions using Azure Databricks. Define best practices, optimize performance, and ensure secure, maintainable deployments. Own Data Platform Architecture Contribute to the design and evolution of the Azure-based data platform, ensuring it meets business, scalability, and reliability requirements. - Ensure Platform Stability & Operations Maintain and support day-to-day operations of the data and cloud infrastructure, proactively monitoring performance, troubleshooting issues, and ensuring high availability. - Implement Best Practices & Governance Establish and enforce standards for cloud architecture, data engineering, security, and cost optimization across Azure services. - Collaborate Across Teams Work closely with data engineers, analysts, DevOps, and business stakeholders to align technical solutions with business needs. - Optimize Performance & Costs Continuously analyze workloads and infrastructure usage to improve efficiency, scalability, and cost-effectiveness within Azure. - Drive Automation & DevOps Practices Implement CI/CD pipelines, infrastructure as code (IaC), and automation for deployment and operational processes. - Provide Technical Leadership Act as a subject matter expert for Azure and Databricks, mentoring team members and guiding technical decisions. - Support Data Engineering Workloads Enable and optimize ETL/ELT pipelines, data ingestion, transformation, and orchestration processes. - Ensure Security & Compliance Apply Azure security best practices, including identity management, access control, and data protection.

Role Description Trinetix is looking for a skilled SQL Senior / Data Engineer + Power BI (L2). Join our team at Trinetix and collaborate on a project with a leading transportation and logistics company in North America, operating a large-scale fleet and relying on complex data platforms and real-time analytics. In this role, you will contribute to maintaining and improving critical data infrastructure by ensuring stability, reliability, and performance of data pipelines and reporting systems. You will work with cloud data platforms, ETL/ELT pipelines, and BI tools, supporting business operations through efficient troubleshooting, monitoring, and data processing. The SQL Senior / Data Engineer owns the data and analytics support queue and is responsible for monitoring, troubleshooting, and resolving failures across cloud data platforms, ETL/ELT pipelines, and Power BI reporting. The role also includes handling SQL-level data fixes and record corrections escalated from application support queues. Note: 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 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 Qualifications - 5+ years in data engineering or data platform support (mandatory) - Hands-on experience with at least 3 of: Azure, AWS, Snowflake, Databricks - Production pipeline support experience is strongly preferred Required Technical Skills - Cloud & Data Platforms: Azure: Data Factory, Azure SQL, Synapse Analytics — 5+ years required; AWS: S3, RDS, Glue — data pipeline and infrastructure support - Data Engineering & Pipelines: Snowflake: query writing, data loading, performance troubleshooting, Snowpipe; Databricks: notebook execution, cluster management, job failure diagnosis, Delta Lake basics; Pipeline tools: Apache Airflow or Azure Data Factory — DAG/pipeline monitoring and repair - BI & Reporting: Power BI: dashboard connectivity, data source troubleshooting, refresh failures, DAX basics - Programming & Tools: SQL: advanced — complex queries, stored procedures, performance tuning across SQL Server and cloud DBs; Python: scripting for data transformation, automation, and diagnostic tasks; Version control: GitLab — CI/CD pipeline basics for data workflows Language Requirements - English - required (all tickets, escalations, client communication) On-Call Requirements - On-call rotation - data incidents - Covers P1/P2 data pipeline and platform failures outside business hours - Shared rotation between Ukraine and Argentina Data Engineers (approx. every other week per person) - Activation required when critical pipeline failures impact business operations or reporting - Response expected within 1 hour of activation - On-call compensation applies per company policy Company Description Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world. Headquartered in Nashville, Tennessee, we have a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. We partner with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture. Our operations are driven by a strong business vision, a people-first culture, and a commitment to responsible growth. We actively give back to the community through various CSR activities and adhere to international principles for sustainable development and business ethics.

• Design, implement, and maintain robust, scalable data pipelines to support AI, analytics, and operational reporting • Own and evolve the data warehouse architecture, ensuring it meets performance, flexibility, and governance needs • Work closely with AI Engineers and BI Engineers to enable advanced modelling, data exploration, and dashboard reliability • Ensure data integrity, availability, lineage, and observability across complex pipelines • Define and enforce best practices in data modelling, pipeline orchestration, and data infrastructure reliability • Champion the use of Infrastructure as Code and automation in managing data services • Proactively address scaling bottlenecks, performance issues, and architectural challenges • Leverage AI tools to accelerate data engineering work — and act as the quality gate on AI-generated pipeline code • Mentor junior Data Engineers and contribute to team knowledge sharing

Lead projects for design, development and maintenance of a data and analytics platform. Effectively and efficiently process, store and make data available to analysts and other consumers. Work with key business stakeholders, IT expects and subject-matter experts to plan, design and deliver optimal analytics and data science solutions. Design and automate deployment of our distributed system for ingesting and transforming data from various types of sources. Design and implement framework to continuously monitor and troubleshoot data quality and data integrity issues. Implement data governance processes and methods for managing metadata, access, retention to data for internal and external users. Design and provide guidance on building reliability, efficient, scalable and quality data pipelines with monitoring and alter mechanisms that combine a variety of sources using ETL/ELT tools or scripting languages. Design and implement physical data models to define the database structure, optimizing database performance through efficient indexing and table relationships. Participate in optimizing, testing, and troubleshooting of data pipelines. Design, develop and operate large scale data storage and processing solutions using different distributed and cloud-based platforms for storing data. Use innovative and modern tools, techniques and architectures to partially or completely automate the most common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity. Assist with renovating the data management infrastructure to drive automation in data integration and management. Ensure the timeliness and success of critical analytics initiatives by using agile development technologies sch as DevOps, Scrum and Kanban. Identify, understand and correct flaws in data that supports effective information governance across operational business processes and decision making. Validate a configuration item change or solution using the Function’s defined best practices, including the Systems Development Life Cycle (SDLC) standards, tools and metrics, to ensure that it works as designed and meets customer requirements. Apply the science of measurement to assess whether a solution meets its intended outcomes using the IT Operating Model (ITOM) to deliver a quality product. Document information and solution based on knowledge gained as part of product development activities. Perform data extract-transform-load (ETL) activities from a variety of sources and transform them for consumption by various downstream applications and users using appropriate tools and technologies. Cummins is an equal opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, or other status protected by law.