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