Data Engineer (AWS)

We are seeking a Data Engineer to join a data initiative in the Group Purchasing Organization (GPO) domain for a global medical technology leader developing innovative devices and therapies across a broad range of clinical areas. In this role, you will work alongside client data owners, architects and governance teams, building pipelines that produce validated partner files today while contributing to the foundation of a longer-term strategic data architecture.

Responsibilities

• Source Analysis &
  • Discovery: Explore existing enterprise data sources (SAP ECC / S4, MDM, product hierarchy data), identify data quality gaps and governance constraints, and help shape the solution design.

• Pipeline Development: Build and maintain pipelines on AWS (including Glue), Snowflake, Informatica and dbt that generate validated GHX files consumed by external partners.
• Data Quality &
  • Validation: Implement data quality checks, validation views and controlled manual intervention points, and support downstream validation in Tableau.

• Team Collaboration: Work in a team of 6 with fellow data engineers, QA engineers and a Data Architect, contributing to technical decisions and code quality.
• Solution Evolution: Help evolve the tactical solution into a strategic one with attention to data quality, lineage and ownership as the project moves from discovery into main delivery and iteration.

Requirements

• Solid commercial experience in hands-on data engineering on cloud-based data platforms.
• Cloud &
  • Data Platform: Practical experience with AWS (including Glue) and Snowflake.

• Transformation &
  • Integration: Hands-on work with dbt for transformations and Informatica (or similar tools) for ingestion and integration.

• Enterprise Data Sources: Experience working with SAP ECC / S4 data and master data (MDM) in complex enterprise landscapes.
• Data Quality &
  • Validation: Experience building validation-heavy pipelines, data quality checks and file-based (CSV) integrations with external partners.

• Collaboration: Ability to work closely with data owners, architects and governance teams and to dig into unfamiliar data independently.

Nice to have

• Solution Design: Experience contributing to technical design in complex enterprise data landscapes.
• Tactical-to-Strategic Mindset: Comfort delivering tactical solutions that later evolve into strategic ones.
• Data Governance: Familiarity with data lineage, ownership models and governance processes.
• BI Validation: Experience using Tableau for downstream consumption or data validation.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team

Competitive salary

Flexible schedule

• Benefits package - medical insurance, sports

Corporate social events

Professional development opportunities

• Well-equipped office

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud &

• DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.