Data Engineer – Databricks/Python

Location: 100% Remote

Job Type: Long Term Contract

Need to give candidate on clients W2

Job Description

What You'll Do

• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals
• Collaborate with data engineers, data consumers, and other team members to come up with simple, functional, and elegant solutions that balance the data needs across the organization
• Solve complex data problems to deliver insights that helps the organization achieve its goals
• Create data products that will be used throughout the organization
• Advise, consult, mentor and coach other data and analytic professionals on data standards and practices
• Foster a culture of sharing, re-use, design for scale stability, and operational e iciency of data and analytic solutions
• Develop and deliver documentation on data engineering capabilities, standards, and processes; participate in coaching, mentoring, design reviews and code reviews
• Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
• Deliver awesome code

What You'll Bring

• 7+ years relevant and progressive data engineering experience
• Deep Technical knowledge and experience in Databricks, Python/Scala, Microsoft Azure architecture and platform including Azure Event Hub and ADF (Azure Data Factory) pipelines
• Hands-on experience working with data pipelines using a variety of source and target locations (e.g., Databricks, SQL Server, Data Lake, file-based, SQL and No-SQL database)
• Thorough knowledge of SQL Server including T-SQL and stored procedures
• Experience in engineering practices such as development, code refactoring, and leveraging design patterns, CI/CD, and building highly scalable data applications and processes
• Experience developing batch ETL pipelines; real-time pipelines are a plus
• Knowledge of advanced data engineering concepts such as dimensional modeling, ETL, data governance, data warehousing involving structured and unstructured data
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. 
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.