Data Architect – Databricks
4 weeks ago
We are seeking a talented and experienced Databricks Architect with a growth mindset and hands-on approach to join our organization.
As a trusted advisor to clients, you will lead the design and implementation of data architectures on Databricks using Azure, AWS, and dbt. You will work closely with clients to understand their data needs, develop customized solutions, and provide strategic guidance on leveraging AI and ML within their data ecosystems.
Key Responsibilities:- Mandatory Skills:
- 5+ years of experience in data architecture, data engineering, or consulting roles.
- Proven expertise in Databricks, Apache Spark, and SQL.
- Proficiency in Python or Scala for data processing and transformation.
- Hands-on experience with Azure Databricks, AWS Databricks, and dbt.
- Strong knowledge of ETL/ELT processes, data warehousing with databricks, and data integration techniques.
- Proven ability to integrate AI/ML models within data pipelines.
- Experience working with clients to develop customized solutions and presenting technical concepts to non-technical stakeholders.
- Excellent problem-solving skills with the ability to troubleshoot complex data issues.
- Strong communication, presentation, and interpersonal skills.
Engage with clients to understand their business challenges, data requirements, and objectives.
Act as a strategic advisor, guiding clients in leveraging Databricks for data engineering, analytics, and machine learning.
Translate client requirements into scalable, robust, and cost-effective data solutions.
Conduct workshops and presentations to demonstrate best practices and innovative solutions.
Solution Design & Implementation:Design and develop scalable data architectures and pipelines using Databricks on Azure and AWS.
Implement ETL/ELT processes using dbt to support data analytics and machine learning applications.
Integrate AI and ML models into data pipelines to provide actionable insights and predictive analytics.
Optimize data workflows to enhance performance, scalability, and cost efficiency.
Implement data governance, data quality, and security best practices in client environments.
Technical Leadership & Collaboration:Lead technical discussions with clients and internal stakeholders to shape solutions.
Provide mentorship to junior engineers and architects within the team.
Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions.
Stay updated on emerging trends and technologies to continuously enhance client solutions.
Education:B.E./B.Tech.
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