Delivery Lead-Data Engineer

Job purpose

The Data Engineer will design, construct, and maintain scalable data management systems using Azure Databricks

This role involves supervising the upkeep of existing data infrastructure workflows and creating data processing pipelines utilizing Databricks Notebooks, Spark SQL, Python, and other Databricks tools

The Senior

Data Engineer will oversee and lead the module through planning, estimation, implementation, monitoring, and tracking

Key responsibilities

5-7 years of experience in software development with a focus on data projects using Python, PySpark, and associated 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

Strong SQL skills with RDMS or NoSQL databases

Experience with developing APIs 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 the 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

In-depth knowledge of data warehousing concepts, architecture, and implementation

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 the ability to work independently or as part of a team

Strong communication and interpersonal skills, with the ability to effectively engage with both technical and non-technical stakeholders

Able to work independently without the need for close supervision and collaboratively as part of cross-team efforts

Key competencies

Interpret business requirements and work with internal resources as well as application vendors

Design, develop, and maintain Data Bricks solutions and relevant data quality rules

Troubleshoot and resolve data-related issues

Configure and create data models and data quality rules to meet customer needs

Handle multiple database platforms like Microsoft SQL Server and Oracle

Review and analyze 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 efficiency and innovative approaches to completing the scope of work

Write clean, efficient, and well-documented code that adheres to best practices and Council IT coding standards

Maintain and operate existing custom code processes

Participate in team problem-solving efforts and offer ideas to solve client issues

Query writing skills with the ability to understand and implement changes to SQL functions and stored procedures

Effectively communicate with business and technology partners, peers, and stakeholders

Deliver results under demanding timelines to real-world business problems

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

Responsible for quality checks and adhering to the agreed Service Level Agreement (SLA) / Turn Around Time (TAT)