Lead Data Engineer
Our customer is one of the biggest property and casualty insurance agencies in the USA that has been providing custom insurance products for real estate investors.
The customer is using an external service to get, store, and manage their data and workflow processes. To improve the process of data governance and data quality there is already an ongoing project to build their own solution that includes importing data from SQL on-premise source and storing it in the Snowflake data warehouse. The expected infrastructure should be built in Microsoft Azure. Data cleansing and transformation are going to be performed in Snowflake as well. Snowflake should be connected to dashboards, Salesforce, and other data consumers if required.
Essential functions
- Lead the design and implementation of data architecture and pipelines on Azure cloud.
- Define and implement best practices for data modeling, schema design, and data integration.
- Evaluate and recommend technologies and tools to support the data infrastructure.
- Build scalable and reliable data pipelines to ingest, transform, and load data from diverse sources into Snowflake or other data warehouses.
- Optimize data pipelines for performance, reliability, and cost-efficiency.
- Coordinate with business stakeholders to prioritize and address data engineering needs.
- Implement data quality checks and validation processes to ensure accuracy and consistency of data.
- Ensure compliance with data governance and security standards.
Qualifications
- Extensive experience with Azure cloud services, particularly in designing and implementing data solutions using Azure Data Services (e.g., Azure Data Factory, Azure Synapse Analytics, Azure Databricks).
- Proficiency in Snowflake data warehouse is highly desirable, including data modeling, schema design, and performance optimization.
- Strong skills in SQL for data querying, manipulation, and optimization.
- Advanced proficiency in Python for data processing, scripting, and automation.
- Familiarity with Java for specific integration needs within the data ecosystem.
- Understanding of data architecture best practices, data governance, and data security principles.
Would be a plus
- Leadership experience in mentoring and guiding a team of data engineers.
- Excellent communication skills with the ability to interact effectively with stakeholders to understand requirements and present solutions.
- Proven ability to translate business requirements into technical specifications and design scalable data solutions.
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.
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