Data Analytics Engineer

UST’s interview process usually starts with a timed online test focusing on aptitude, SQL queries, and basic Python coding. The technical interview dives deeper into data modeling, dashboard design, and scenario‑based problem solving. The HR round assesses cultural fit, communication skills, and career aspirations. Preparing with real‑world reporting case studies and practicing SQL joins can boost confidence.

UST promotes a collaborative and inclusive work environment where learning is encouraged through regular training programs and mentorship. Employees enjoy a balanced work‑life schedule, flexible remote options, and clear career progression pathways, making it a supportive place for fresh talent to grow.

Bachelor’s degree in Computer Science, Information Technology, Electronics, or any related engineering discipline. Minimum 60% aggregate (or CGPA 6.0/10). Fresh graduates from the 2023‑2025 batches are preferred. No active backlogs at the time of joining. Strong logical reasoning and communication skills are essential.

Round 1: Online aptitude & coding test → Round 2: Technical interview (SQL, Python, reporting tools) → Round 3: HR interview (fitment, culture, salary discussion)

UST (formerly known as UST Global) is a leading digital transformation partner with a presence in more than 30 countries and a workforce of over 30,000 professionals. The company helps Fortune 500 clients across industries such as banking, healthcare, manufacturing, and technology to reinvent their businesses through innovative solutions, cloud services, and data-driven insights. With a strong focus on culture, UST promotes humility, humanity, and integrity, fostering an environment where employees can grow, collaborate, and make a tangible impact on billions of lives. The organization’s commitment to diversity, inclusion, and continuous learning makes it an attractive destination for fresh talent looking to start a meaningful career. The Reporting & Analytics Engineer role is designed for fresh graduates who are passionate about turning raw data into actionable business intelligence. As a member of the analytics team, you will be responsible for gathering reporting requirements from stakeholders, designing and developing operational and management dashboards, and building automated data pipelines that ensure timely and accurate delivery of insights. You will work closely with data engineers, application teams, and business users to create reusable reporting components, troubleshoot data quality issues, and support production reporting environments. The role offers exposure to a wide range of technologies, including Python, advanced SQL, Power BI/Tableau, and workflow orchestration tools, making it an excellent launchpad for a career in data engineering and analytics. Key responsibilities include: 1. Interacting with business users to capture and document reporting requirements. 2. Designing and developing interactive dashboards using Power BI, Tableau, or similar tools. 3. Building and maintaining automated ETL/ELT workflows with scheduling capabilities. 4. Developing data transformation logic and aggregation layers for KPI computation. 5. Creating reusable data models and datasets for enterprise-wide consumption. 6. Monitoring and troubleshooting reporting jobs, ensuring data quality and timeliness. 7. Conducting root‑cause analysis for reporting failures and implementing preventive measures. 8. Preparing technical documentation and knowledge‑transfer material for support teams. 9. Collaborating with data engineers to integrate new data sources via REST APIs, JSON, XML, and file‑based feeds. 10. Staying updated with emerging analytics tools and best practices to continuously improve the reporting ecosystem. The tech stack revolves around Python, advanced SQL, relational databases (SQL Server, Oracle, PostgreSQL, MySQL), reporting platforms (Power BI, Tableau, Qlik Sense, Looker, SSRS, Grafana), workflow tools (Apache Airflow), and version control (Git). Candidates with exposure to cloud data warehousing, authentication/authorization mechanisms, and Linux/Windows server environments will find additional growth opportunities. Growth path at UST typically moves from Reporting Engineer to Senior Analyst, then to Analytics Lead or Data Platform Architect, with ample scope for cross‑functional moves into data science or solution architecture. Joining UST provides a chance to work on large‑scale enterprise projects, receive mentorship from seasoned professionals, and benefit from a culture that values learning, innovation, and work‑life balance.