Job
Description
About the Job The Director Data Engineering will lead the development and implementation of a comprehensive data strategy that aligns with the organization’s business goals and enables data driven decision making. Roles and Responsibilities Build and manage a team of talented data managers and engineers with the ability to not only keep up with, but also pioneer, in this space Collaborate with and influence leadership to directly impact company strategy and direction Develop new techniques and data pipelines that will enable various insights for internal and external customers Develop deep partnerships with client implementation teams, engineering and product teams to deliver on major cross-functional measurements and testing Communicate effectively to all levels of the organization, including executives Provide success in partnering teams with dramatically varying backgrounds, from the highly technical to the highly creative Design a data engineering roadmap and execute the vision behind it Hire, lead, and mentor a world-class data team Partner with other business areas to co-author and co-drive strategies on our shared roadmap Oversee the movement of large amounts of data into our data lake Establish a customer-centric approach and synthesize customer needs Own end-to-end pipelines and destinations for the transfer and storage of all data Manage 3rd-party resources and critical data integration vendors Promote a culture that drives autonomy, responsibility, perfection and mastery. Maintain and optimize software and cloud expenses to meet financial goals of the company Provide technical leadership to the team in design and architecture of data products and drive change across process, practices, and technology within the organization Work with engineering managers and functional leads to set direction and ambitious goals for the Engineering department Ensure data quality, security, and accessibility across the organization Skills You Will Need 10+ years of experience in data engineering 5+ years of experience leading data teams of 30+ resources or more, including selection of talent planning / allocating resources across multiple geographies and functions. 5+ years of experience with GCP tools and technologies, specifically, Google BigQuery, Google cloud composer, Dataflow, Dataform, etc. Experience creating large-scale data engineering pipelines, data-based decision-making and quantitative analysis tools and software Experience with hands-on to code version control systems (git) Experience with CICD, data architectures, pipelines, quality, and code management Experience with complex, high volume, multi-dimensional data, based on unstructured, structured, and streaming datasets Experience with SQL and NoSQL databases Experience creating, testing, and supporting production software and systems Proven track record of identifying and resolving performance bottlenecks for production systems Experience designing and developing data lake, data warehouse, ETL and task orchestrating systems Strong leadership, communication, time management and interpersonal skills Proven architectural skills in data engineering Experience leading teams developing production-grade data pipelines on large datasets Experience designing a large data lake and lake house experience, managing data flows that integrate information from various sources into a common pool implementing data pipelines based on the ETL model Experience with common data languages (e.g. Python, Scala) and data warehouses (e.g. Redshift, BigQuery, Snowflake, Databricks) Extensive experience on cloud tools and technologies - GCP preferred Experience managing real-time data pipelines Successful track record and demonstrated thought-leadership and cross-functional influence and partnership within an agile / water-fall development environment. Experience in regulated industries or with compliance frameworks (e.g., SOC 2, ISO 27001). Nice to have: HR services industry experience Experience in data science, including predictive modeling Experience leading teams across multiple geographies Show more Show less
