Business Technology Analyst
Thomson Reuters View all jobs
- Hyderabad, Telangana
- Permanent
- Full-time
- SQL Proficiency a must
- 6+ years' experience in data engineering with a strong focus on data transformation and analytics engineering
- Strong experience with dbt (data build tool) highly preferred
- Experience with data pipeline and transformation tools such as dbt, Glue, FiveTran, Alteryx or similar solutions
- Hands-on experience with CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab, etc.) and strong familiarity with version control best practices, code reviews, and documentation standards.
- Familiarity with Agile development practices, including sprint planning, backlog grooming, iterative delivery, and cross-functional collaboration
- Experience with data orchestration tools like Airflow or Dagster (DPOT)
- Experience using cloud-based data warehouse solutions such as Snowflake, Redshift, Azure
- Preferred experience using Amazon Web Services (S3, Glue, Athena, QuickSight)
- Strong data modelling expertise with various schemas like snowflake and star
- Proven track record designing and implementing data transformation logic and workflows
- Experience building complex data models that support analytics and reporting needs
- Knowledge of database design and query optimization
- Experience with a scripting language like Python
- Works well within a team and collaborates with colleagues across domains and geographies
- Excellent oral, written, and visual communication skills
- Has a demonstrable ability to assimilate new information thoroughly and quickly
- Strong logical and scientific approach to problem-solving
- Can articulate complex results in a simple and concise manner to all levels within the organization
- Build and maintain sophisticated data models using tools like dbt to ensure data quality, consistency, and accessibility Hands-on experience with CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab, etc.) and strong familiarity with version control best practices, code reviews, and documentation standards.
- Experience designing scalable and maintainable data architectures, aligned with engineering standards and long-term platform growth.
- Leverage orchestration tools (Airflow, Dagster) to schedule and monitor data transformation workflows
- Ability to mentor junior engineers and share industry best practices in data engineering, data modeling, and pipeline development
- Work closely with data scientists and data visualization teams to understand data requirements to ensure the availability of high-quality, well-transformed data for analytics, modelling, and reporting
- Strong troubleshooting and optimization skills, with experience improving pipeline performance, reliability, and cloud cost efficiency.
- Contribute to the strategy and architecture of data management systems and solutions
- Proactively troubleshoot and resolve data transformation, data quality, and performance bottlenecks in a timely manner
- Be open to learning and working on emerging technologies in data engineering, analytics engineering, data science and cloud computing space
- Have the curiosity to interrogate data, conduct independent research, utilize various techniques, and tackle ambiguous problems
- Self‑driven and proactive, able to work with minimal supervision, take ownership of deliverables, and step up to additional responsibilities as business needs evolve