Sr. Data Engineer

This position can ONLY consider W2 candidates. C2C/1099 candidates are not eligible to be hired for this opportunity. Title: Sr. Data Engineer Term: Contract – 12 months extendable Must be open to working PST hours Data Engineer – Databricks/Python 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 efficiency 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.