Virtusa helps its Clients by becoming a true extension of their software and data development capabilities. Through the readily set up, comprehensive, and self-governing teams, we let our Clients focus on their business while we make sure that their software products and data tools scale up accordingly and with outstanding quality.
We are looking for experienced team players to fill the position of Data Analyst and participate in our up-and-coming project for our client from the healthcare area. This is a hybrid model with 2 days from the client's Warsaw office.
You can expect to:
- Design and implement conceptual, logical, and physical data models for enterprise data platforms
- Collaborate with business stakeholders, data architects, data engineering teams, and analytics teams to gather and translate business requirements into scalable data structures
- Develop and optimize data models for data warehouses, data lakes, and lakehouse architectures
- Perform data analysis, data profiling, data validation, and quality assessments to ensure accuracy and consistency
- Work with ETL/ELT and Data Engineering teams to ensure proper data mapping, transformation, and integration across multiple source systems
Requirements
- Strong experience in Data Engineering, data modeling, data analysis, and enterprise data architecture
- Expertise in relational and dimensional data modeling (Star/Snowflake schemas)
- Deep understanding of data warehousing, data lakes, and lakehouse concepts
- Hands-on experience with databases such as SQL Server, Oracle, PostgreSQL, Snowflake, and Redshift
- Strong SQL programming, query optimization, and analytical skills
- Hands-on experience in ETL/ELT development using DBT and tools such as Informatica, Talend, Azure Data Factory, AWS Glue, or similar
- Experience designing and supporting distributed data systems and scalable cloud-based data platforms
- Strong exposure to CI/CD pipelines and version control tools such as Git, Jenkins, GitHub Actions, Azure DevOps
- Hands-on experience with AWS data services including AWS Glue, S3, Redshift, Lambda, Athena, and EMR
- Experience with cloud platforms such as AWS, Azure, or GCP
- Proficiency in data modeling and metadata management tools such as ERwin, ER/Studio, PowerDesigner, or similar
- Familiarity with data governance, catalog, and lineage tools such as Collibra, Alation, Apache Atlas, or Informatica EDC
- Experience working in Agile/Scrum environments
- Experience working closely with Data Engineering teams on enterprise-scale data transformation and modernization programs
Good to Have / Preferred Technical Skills:
- Hands-on experience with big data technologies such as Spark, Databricks, Hadoop, or Kafka
- Experience with Python or PySpark for data analysis, transformation, and automation
- Exposure to BI and reporting tools such as Power BI, Tableau, or QuickSight
- Knowledge of APIs, microservices-based data integration, and real-time/streaming data pipelines
- Experience with Infrastructure as Code (Terraform, CloudFormation) and container technologies such as Docker or Kubernetes
- Understanding of Data Vault 2.0 modeling concepts
- Exposure to AI/ML data preparation pipelines and feature engineering concepts
- Experience in Pharma, Healthcare, or Life Sciences domains will carry strong preference
- R&D or innovation-focused project experience is good to have
Benefits
- Professional training programs
- Work with a team that is recognized for its excellence. We have been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We have also received the Great Place To Work® certification for seven years in a row
