Grid Dynamics
Client is a leading American fast‑food restaurant chain renowned for its high‑quality chicken products and exceptional customer service. The brand is expanding its digital capabilities by seeking innovative data solutions to streamline operations and drive business insights.
Requirements Experience
Minimum 5 years of proven, hands‑on experience as a Data Architect working with Databricks in production environments.
Technical Expertise
Advanced knowledge of Apache Spark, AWS Glue, Apache Airflow, and Kafka (or similar streaming technologies).
Strong proficiency in Python for data engineering and automation tasks.
Solid understanding of AWS architecture, including networking, storage, and compute services.
Experience designing and implementing data lakehouse and medallion architectures (raw → silver → gold).
Proven ability to define data movement and transformation patterns for both batch and streaming pipelines.
Familiarity with integrating low‑latency and event‑driven systems (e.g., Redpanda, Benthos) into enterprise data ecosystems.
Data Quality & Governance
Experience implementing data quality frameworks, observability, and monitoring tools.
Strong understanding of data governance principles and metadata management.
Leadership & Communication
Ability to guide and mentor engineers and analysts on data architecture best practices.
Excellent communication skills to collaborate with technical and non‑technical stakeholders.
Nice to Have
Experience with on‑premise‑to‑cloud migrations.
Familiarity with CI/CD for data pipelines and infrastructure‑as‑code (e.g., Terraform, CloudFormation).
Responsibilities
Lead the architecture and design of new data movement and transformation patterns leveraging Databricks, Spark, and AWS services.
Define and implement ETL/ELT frameworks supporting both low‑latency (Redpanda) and batch (Benthos) data ingestion.
Collaborate with the Delivery Manager and client stakeholders to define the target state architecture and migration strategy from legacy data flows.
Establish and enforce data product standards and contribute to the internal data delivery framework ensuring high‑quality, reusable datasets.
Oversee data quality, observability, and monitoring solutions to ensure reliability and trust in the data.
Provide technical leadership to the data engineering team—reviewing, optimizing pipelines, and ensuring adherence to architectural principles.
Evaluate and document the current data environment, identify gaps, and propose scalable, cost‑efficient improvements.
Stay aligned with enterprise standards while introducing innovative architectural solutions that improve latency, scalability, and maintainability.
Support knowledge transfer and capability building within the client’s team to ensure long‑term sustainability of the solution.
We offer
Opportunity to work on bleeding‑edge projects
Work with a highly motivated and dedicated team
Benefits package – medical insurance, sports
Corporate social events
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.
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Requirements Experience
Minimum 5 years of proven, hands‑on experience as a Data Architect working with Databricks in production environments.
Technical Expertise
Advanced knowledge of Apache Spark, AWS Glue, Apache Airflow, and Kafka (or similar streaming technologies).
Strong proficiency in Python for data engineering and automation tasks.
Solid understanding of AWS architecture, including networking, storage, and compute services.
Experience designing and implementing data lakehouse and medallion architectures (raw → silver → gold).
Proven ability to define data movement and transformation patterns for both batch and streaming pipelines.
Familiarity with integrating low‑latency and event‑driven systems (e.g., Redpanda, Benthos) into enterprise data ecosystems.
Data Quality & Governance
Experience implementing data quality frameworks, observability, and monitoring tools.
Strong understanding of data governance principles and metadata management.
Leadership & Communication
Ability to guide and mentor engineers and analysts on data architecture best practices.
Excellent communication skills to collaborate with technical and non‑technical stakeholders.
Nice to Have
Experience with on‑premise‑to‑cloud migrations.
Familiarity with CI/CD for data pipelines and infrastructure‑as‑code (e.g., Terraform, CloudFormation).
Responsibilities
Lead the architecture and design of new data movement and transformation patterns leveraging Databricks, Spark, and AWS services.
Define and implement ETL/ELT frameworks supporting both low‑latency (Redpanda) and batch (Benthos) data ingestion.
Collaborate with the Delivery Manager and client stakeholders to define the target state architecture and migration strategy from legacy data flows.
Establish and enforce data product standards and contribute to the internal data delivery framework ensuring high‑quality, reusable datasets.
Oversee data quality, observability, and monitoring solutions to ensure reliability and trust in the data.
Provide technical leadership to the data engineering team—reviewing, optimizing pipelines, and ensuring adherence to architectural principles.
Evaluate and document the current data environment, identify gaps, and propose scalable, cost‑efficient improvements.
Stay aligned with enterprise standards while introducing innovative architectural solutions that improve latency, scalability, and maintainability.
Support knowledge transfer and capability building within the client’s team to ensure long‑term sustainability of the solution.
We offer
Opportunity to work on bleeding‑edge projects
Work with a highly motivated and dedicated team
Benefits package – medical insurance, sports
Corporate social events
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.
#J-18808-Ljbffr