Senior profile (Staff level), capable of driving technical decisions.
Engineering: Expert Python, SQL, and robust Data Pipeline building.
Dashboards: Strong experience with
Apache Superset (building analytics datasets and visualizations).
ML Context: Solid understanding of ML lifecycles to support the team.
Soft Skills: Excellent communication is critical.
Responsibilities
Key Responsibilities
- End-to-End Pipeline Ownership: Architect, build, and maintain robust, scalable data pipelines using Python and SQL to support both analytics and machine learning workflows.
- Analytics & Visualization Leadership: Serve as the Subject Matter Expert (SME) for Apache Superset. Design and manage complex datasets, semantic layers, and high-impact dashboards that drive business decisions.
- Bridge Data & ML: Act as the strategic link between Data Engineering and ML teams, ensuring that data infrastructure supports the full ML lifecyclefrom feature engineering and training to inference and monitoring.
- Technical Strategy & Architecture: Drive high-level technical decisions regarding data modeling, warehouse architecture, and tool selection (AWS/GCP ecosystems), balancing performance, cost, and scalability.
- Data Quality & Governance: Establish and enforce best practices for data quality, lineage, and observability to ensure trust in data across the organization.
- Mentorship & Collaboration: Mentor senior and mid-level engineers, fostering a culture of engineering excellence, and communicate complex technical concepts effectively to PMs, executives, and non-technical stakeholders.
Requirements
Role: Staff /Lead Data Engineer (ML & Analytics)
Must-Haves
Seniority: Senior profile (Staff level), capable of driving technical decisions.
Engineering: Expert Python, SQL, and robust Data Pipeline building.
Dashboards: Strong experience with
Apache Superset (building analytics datasets and visualizations).
ML Context: Solid understanding of ML lifecycles to support the team.
Soft Skills: Excellent communication is critical.
Nice-to-Have
Airflow, Cloud platforms (AWS/GCP).
Nice to have
Airflow, Cloud platforms (AWS/GCP).
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.
