Job Description

Job Purpose

Design, construct, and maintain scalable data management systems using Azure Databricks, ensuring they meet end-user expectations. Supervise the upkeep of existing data infrastructure workflows to ensure continuous service delivery. Create data processing pipelines utilizing Databricks Notebooks, Spark SQL, Python and other Databricks tools. Oversee and lead the module through planning, estimation, implementation, monitoring and tracking.

Desired Skills and experience

? 5+ years of experience in software development using Python, PySpark and its frameworks.
? Proven experience as a Data Engineer with experience in Azure cloud.
? Experience implementing solutions using - Azure cloud services, Azure Data Factory, Azure Lake Gen 2, Azure Databases, Azure Data Fabric, API Gateway management, Azure Functions
? Design, build, test, and maintain highly scalable data management systems using Azure Databricks
? Strong SQL skills with RDMS or noSQL databases
? Experience with developing API's using FastAPI or similar frameworks in Python
? Familiarity with the DevOps lifecycle (git, Jenkins, etc.), CI/CD processes
? Good understanding of ETL/ELT processes
? Experience in financial services industry, financial instruments, asset classes and market data are a plus.
? Assist stakeholders with data-related technical issues and support their data infrastructure needs.
? Develop and maintain documentation for data pipeline architecture, development processes, and data governance.
? Data Warehousing: In-depth knowledge of data warehousing concepts, architecture, and implementation, including experience with various data warehouse platforms.
? Extremely strong organizational and analytical skills with strong attention to detail
? Strong track record of excellent results delivered to internal and external clients.
? Excellent problem-solving skills, with ability to work independently or as part of team.
? Strong communication and interpersonal skills, with ability to effectively engage with both technical and non-technical stakeholders.
? Able to work independently without the needs for close supervision and collaboratively as part of cross-team efforts.

Key responsibilities include:

Interpret business requirements, either gathered or acquired. Work with internal resources as well as application vendors Designing, developing, and maintaining Data Bricks Solution and Relevant Data Quality rules Troubleshooting and resolving data related issues. Configuring and Creating Data models and Data Quality Rules to meet the needs of the customers. Hands on in handling Multiple Database platforms. Like Microsoft SQL Server, Oracle etc Reviewing and analyzing data from multiple internal and external sources Analyze existing PySpark/Python code and identify areas for optimization. Write new optimized SQL queries or Python Scripts to improve performance and reduce run time. Identify opportunities for efficiencies and innovative approaches to completing scope of work. Write clean, efficient, and well-documented code that adheres to best practices and Council IT coding standards. Maintenance and operation of existing custom codes processes Participate in team problem solving efforts and offer ideas to solve client issues. Query writing skills with ability to understand and implement changes to SQL functions and stored procedures. Effectively communicate with business and technology partners, peers and stakeholders Ability to deliver results under demanding timelines to real-world business problems. Ability to work independently and multi-task effectively. Configure system settings and options and execute unit/integration testing. Develop end-user Release Notes, training materials and deliver training to a broad user base. Identify and communicate areas for improvement. Demonstrate high attention to detail, should work in a dynamic environment whilst maintaining high quality standards, a natural aptitude to develop good internal working relationships and a flexible work ethic. Responsible for Quality Checks and adhering to the agreed Service Level Agreement (SLA) / Turn Around * Time (TAT)