What are the responsibilities and job description for the Lead Azure Databricks Data Engineer - 10+ Years Exp Only position at AQUA Information Systems, Inc.?
Job Details
Responsibilities:
Design and build data pipelines and applications to stream and process datasets at low latencies, ensuring high performance and reliability.
Write and optimize complex SQL queries to support various data processing tasks and analytical needs.
Create complex data models and design ETL processes that cater to business requirements while utilizing large databases effectively.
Utilize Big Data technologies like Spark, Kafka, and Hive to handle and process large datasets.
Implement solutions using Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service to build robust data processing architectures.
Design and implement data pipelines using API ingestion and streaming ingestion methods to ensure timely data availability.
Apply knowledge of DevOps processes, including CI/CD and Infrastructure as Code (IaC), to automate deployment and management of data solutions.
Develop NoSQL solutions using Azure Cosmos DB to support diverse data storage needs.
Manage and optimize data storage solutions using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Cosmos DB.
Monitor and troubleshoot data-related issues within the Azure environment to maintain high availability and performance.
Implement data security measures, including encryption, access controls, and auditing, to protect sensitive information.
Automate data pipelines and workflows to streamline data ingestion, processing, and distribution tasks.
Leverage Azure's analytics services, such as Azure Synapse Analytics, to extract insights and support data-driven decision-making.
Document data procedures, systems, and architectures to maintain clarity and ensure compliance with regulatory standards.
Provide guidance and support for data governance initiatives, including metadata management, data lineage, and data cataloging.
Requirements:
You are:
10 years of experience in data engineering, specifically with Azure technologies and Big Data solutions.
Expert-level skills in writing and optimizing complex SQL queries.
Strong experience with complex data modeling and ETL design in business environments.
Fluent with technologies such as Spark, Kafka, and Hive.
In-depth knowledge of Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service.
Proven experience in designing and building data pipelines with API and streaming ingestion methods.
Solid understanding of DevOps processes (CI/CD) and Infrastructure as Code.
Experience in developing NoSQL solutions using Azure Cosmos DB.
Thorough understanding of Azure and AWS Cloud Infrastructure offerings.
Working knowledge of Python is desirable.
Familiarity with data security measures and best practices.
It would be great if you also had:
Relevant certifications in Azure Data Engineering or Data Science.
Knowledge of visualization tools like Power BI for reporting and analytics.
Familiarity with machine learning concepts and their application in data processing.
