Director of Data Engineering
Onsite and remote work involving the use of a laptop and frequent phone calls. Job summary The Director of Data Engineering will have overall responsibility for data engineering including IT engineering support for data intake, data clean-up, processing and management to support Client Services matters. Data engineering areas of activity include compliance with data security measures, data validation, data clean-up, data summarization and data processing performance optimization. This position will have data engineering project management responsibilities across multiple concurrent large-scale projects. This position must have a client service focus and must communicate and coordinate effectively with Client Services Project Supervisors across multiple projects. The Director of Data Engineering will have proven strong skills in project management, big data techniques, data wrangling, cloud computing, hybrid-cloud, R, Spark, Python, SQL and related skills. Essential functions Manage a team of data engineering staff. Collaborate effectively across the Technical Services, Client Services and Operations teams. Establish and manage optimal data engineering workflows in collaboration with Client Services Project Supervisors to meet the needs of client matters. These workflows could include use of R, Spark, Python and SQL utilizing optimized cloud, on-premise and hybrid-cloud resources. Guidance and direction to the firm on data engineering best practices, tools and methods, including use of cloud, on-premise and hybrid-cloud resources. Assure compliance with Data Security measures and controls as established by the Chief Information Security Officer. Coordinate data engineering activities to assure speed, accuracy and effectiveness of data access and processing. Lead data engineering staff and collaborate with consultants to assure effective data engineering and processing methods. Reports to work on a regular basis, and is available for occasional after hours emergency calls and projects. Job summary Eight or more years of responsibility managing data engineering projects involving multiple complex, big data matters. Proven project management experience and capabilities in an environment that includes onpremise and cloud processing. Proven experience in data engineering and big data methods and tools including R, Spark, Python, SQL, ETL, Databricks, Snowflake, Cloudera Data Platform, hybrid-cloud and other related tools and techniques. Proven ability to optimize compute processing speed and performance in multiple and varied usecases and to troubleshoot and resolve processing challenges. Proven experience operating in an environment that includes extensive security controls and compliance with standards such as HITRUST, NIST, SOC2 and ISO 9000. Knowledge of machine learning, regression, statistics and other analytical processes. Experience with data modeling, integration, and warehousing. Ability to communicate and document technical topics for non-technical staff. Ability to develop and mentor staff. Ability to establish standards and best practices. Ability to identify, evaluate and recommend new tools and methods as needed to keep practices up to date and competitive. Strong problem solving and data analysis skills. Data visualization tools (in R, Shiny, Tableau, etc.). Ability to operate a computer or other office productivity machinery. Ability to perform essential functions with or without a reasonable accommodation. May require more than 40.0 hours per week to perform the essential duties of the position.