Databricks Solutions Architect
3 weeks ago
Job Title: Databricks Solutions Architect
We're seeking an experienced Databricks Expert/Architect to join Tiger Analytics's data services team. This role will play a key part in designing, implementing, and optimizing Databricks solutions across the organization.
Key Responsibilities:
- Analyze business requirements and translate them into technical specifications for data pipelines, data lakes, and analytical processes on the Databricks platform.
- Design and architect end-to-end data solutions, including data ingestion, storage, transformation, and presentation layers, to meet business needs and performance requirements.
- Lead the setup, configuration, and optimization of Databricks clusters, workspaces, and jobs to ensure the platform operates efficiently and meets performance benchmarks.
- Manage access controls and security configurations to ensure data privacy and compliance.
- Design and implement data integration processes, ETL workflows, and data pipelines to extract, transform, and load data from various sources into the Databricks platform.
- Optimize ETL processes to achieve high data quality and reduce latency.
- Monitor and optimize query performance and overall platform performance to ensure efficient execution of analytical queries and data processing jobs.
- Identify and resolve performance bottlenecks in the Databricks environment.
- Establish and enforce best practices, standards, and guidelines for Databricks development, ensuring data quality, consistency, and maintainability.
- Implement data governance and data lineage processes to ensure data accuracy and traceability.
- Mentor and train team members on Databricks best practices, features, and capabilities.
- Conduct knowledge-sharing sessions and workshops to foster a data-driven culture within the organization.
- Will be responsible for Databricks Practice Technical/Partnership initiatives.
- Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
Requirements:
- Strong in Unity Catalog, Delta Lake, dbConnect, db API 2.0
- Databricks workflow orchestration, Security management, Platform governance, and Data Security
- Must know new features available in Databricks and their implications along with various possible use cases.
- Must have followed various architectural principles to design best suited per problem.
- Must be well-versed with Databricks Lakehouse concept and its implementation in enterprise environments.
- Must have a strong understanding of Data warehousing and various governance and security standards around Databricks.
- Must know about cluster optimization and its integration with various cloud services.
- Must have a good understanding of creating complex data pipelines.
- Must be strong in SQL and Spark-SQL.
- Must have strong performance optimization skills to improve efficiency and reduce cost.
- Must have worked on designing both Batch and streaming data pipelines.
- Must have extensive knowledge of Spark and Hive data processing frameworks.
- Must have worked on any cloud (Azure, AWS, GCP) and most common services like ADLS/S3, ADF/Lambda, CosmosDB/DynamoDB, ASB/SQS, and Cloud databases.
- Must be strong in writing unit test cases and integration tests.
- Responsible for setting best practices around Databricks CI/CD.
- Must understand composable architecture to take fullest advantage of Databricks capabilities.
- Good to have Rest API knowledge.
- Good to have an understanding of cost distribution.
- Good to have if worked on a migration project to build a Unified data platform.
- SQL Endpoint – Photon engine
- Hands-on Experience to design and build Databricks-based solutions on any cloud platform.
- Must be very good at designing End-to-End solutions on cloud platforms.
- Must have good knowledge of Data Engineering concepts and related services of the cloud.
- In-depth hands-on implementation knowledge of Databricks. Delta Lake, Delta table - Managing Delta Tables, Delta live tables, Databricks Cluster Configuration, Cluster policies.
- Experience handling structured and unstructured datasets
- Strong proficiency in programming languages like Python, Pyspark, Scala, or SQL.
- Experience with Cloud platforms like AWS understanding of cloud-based data storage and computing services.
- Familiarity with big data technologies like Apache Spark, Hadoop, and data lake architectures.
- Develop and maintain data pipelines, ETL workflows, and analytical processes on the Databricks platform.
- Should have good experience in Data Engineering in Databricks Batch process and Streaming
- Should have good experience in creating Workflows & Scheduling pipelines.
- Should have good exposure to how to make packages or libraries available in DB.
- Familiarity with Databricks default runtimes
- Databricks Certified Data Engineer Associate/Professional Certification (Desirable).
- Should have experience working in Agile methodology
- Strong verbal and written communication skills.
- Strong analytical and problem-solving skills with a high attention to detail.
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