An international law firm is looking for a Data Engineer to join their team in NYC. 

Compensation: $115-160k

The Data Engineer is responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection. The Data Engineer is an experienced data pipeline builder who enjoys optimizing data systems and building them from the ground up. This individual will support our software developers, architects, and data owners across various data initiatives and ensures an optimal and consistent data delivery architecture. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.

Responsibilities:

Design, construct, test and maintain data architectures and data pipelines Ensure our data architecture supports the requirements of the business Develop custom data models and algorithms to apply to data sets Assess the effectiveness and accuracy of new data sources and data gathering techniques. Client opportunities for data acquisition Develop data set processes for data modeling, mining and production Employ a variety of languages and tools to marry systems together Recommend ways to improve data reliability, efficiency and quality Leverage large volumes of data from internal and external sources to answer business demands Introduce automation through effective metadata management and using innovative and modern tools and techniques. Partially or completely automate the most common and repeatable data preparation and integration tasks Propose appropriate data ingestion, preparation, integration and operationalization techniques in addressing data requirements Lead the development of data governance policies and best practices for consumers and users of data we provision Coordinate with different functional teams to implement models and monitor outcomes Develop processes and tools to monitor and analyze model performance and data accuracy

Qualifications:

A Bachelor's or Master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field or equivalent work experience At least five years' experience in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks At least three years' experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative Excellent communication and collaboration skills Excellent problem solving and analytical skills Must be highly effective within a collaborative environment Must be able to independently resolve issues and efficiently self-direct work activities based on the ability to capture, organize, and analyze information Demonstrates knowledge of the following processes, tools or applications Experienced in designing, building and managing data pipelines for data structures Expertise with advanced analytics tools for Object-oriented/object function scripting. Includes languages such as C#, Python and others Expert in SQL, PL/SQL, SSIS and SSAS Knowledge and/or certifications on upcoming NoSQL/Hadoop-oriented databases like MongoDB, Cassandra, and others for non-relational databases Experienced working with large, heterogeneous data sets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies Experienced working with popular data discovery, analytics and BI software tools such as Tableau, Power BI and others Experienced working with data governance/data quality and data security teams Experienced employing Microsoft MDM (Master Data Management) and MDS Ability to troubleshoot complicated issues across multiple systems and driving solutions Effectively convey technical concepts to non-technical individuals Demonstrate a high level of Data Security Awareness Experience with financial and legal industry data is a plus