Data Architect

Essential functions

Key Responsibilities

• Design and own end‑to‑end data architectures including data lakes, data warehouses, and streaming pipelines using big data technologies (e.g., Spark, Kafka, Hive) on public cloud platforms.

• Define canonical data models, integration patterns, and governance standards to ensure data quality, security, and compliance across the organization.

• Lead presales activities: assess client requirements, run discovery workshops, define solution blueprints, size and estimate effort, and contribute to RFP/RFI responses and proposals.

• Build and review PoCs/accelerators using SQL and Python (e.g., PySpark, notebooks) to demonstrate feasibility, performance, and business value to customers.

• Collaborate with data engineers, BI/ML teams, and application architects to ensure the designed architecture is implemented as intended and is cost‑efficient, scalable, and reliable.

• Establish best practices for data security, access control, and lifecycle management in alignment with regulatory and enterprise policies.

• Monitor and continuously optimize data platforms for performance, reliability, and cost, leveraging cloud‑native services and observability tools.

• Provide architectural guidance and mentoring to engineering teams; review designs and code for critical data components.

Required Skills & Experience

• 12-16 years of overall experience in data engineering/analytics, with 4+ years as a Data/Big Data Architect.

• Strong expertise in SQL (analytical queries, performance tuning) and Python for data processing and automation.

• Hands‑on experience with big data frameworks and tools such as Spark, Kafka, Hadoop ecosystem, distributed file systems, and modern ETL/ELT pipelines.

• Practical experience on at least one major cloud platform (AWS, Azure, or GCP) with services such as data lakes, warehouse services (Redshift/Snowflake/BigQuery/Synapse), and orchestration tools.

• Proven presales exposure: client workshops, solution design, RFP/RFI responses, effort estimation, and building PoCs or demos.

• Strong understanding of data modeling (OLTP, OLAP, dimensional modeling), data governance, security, and compliance.

• Ability to communicate complex data solutions clearly to both technical and business stakeholders.

Qualifications

• Design and own end‑to‑end data architectures including data lakes, data warehouses, and streaming pipelines using big data technologies (e.g., Spark, Kafka, Hive) on public cloud platforms.

• Define canonical data models, integration patterns, and governance standards to ensure data quality, security, and compliance across the organization.

• Lead presales activities: assess client requirements, run discovery workshops, define solution blueprints, size and estimate effort, and contribute to RFP/RFI responses and proposals.

Would be a plus

• Ability to communicate complex data solutions clearly to both technical and business stakeholders.

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.