GREAT Permanent opportunity with a FULL suite of benefits
Title: Data Engineering Leader
Location: Remote with occasional travel
Your expertise in data engineering, software engineering, and machine learning will enable and empower our organization to build and deploy data driven solutions to production. You will be a champion of DataOps, DevOps, and agile practices; leading project teams and mentoring team members to realize their full potential.
- Leadership: Develop and lead a team of Data Engineers in collaboration with Data Science, Data Warehousing, and Business Intelligence to create, test, scale and monitor enterprise class data pipelines. Cultivate a generative culture that values continuous improvement through experimentation and self-guided learning. Ensure agile teams are properly staffed to deliver on time by defining clear data engineering strategies and principles, maintaining a roadmap for execution, and actively secure its implementation through the scrum process.
- Team Development/Coaching: Act as a positive coach/mentor for broader organization to develop stronger understanding of the data architecture and software design patterns that create scalable, maintainable, well-designed analytics solutions. Acts as a facilitator of complex technical topics that require cross-functional consultation.
- Architecture: Relentlessly identify and remove friction in the data engineering development lifecycle to improve developer experience and increase velocity. Influence, develop, and sustain large-scale analytics architecture required for delivering Data Engineering work product. Establish software architecture and software design patterns to write scalable, maintainable, well-designed code. Research and evaluate tools in data transformation, automated CI/CD, data quality monitoring, and data serving.
- Agile Project Work: Work in cross-functional, geographically distributed agile teams of highly skilled data engineers, software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate analytic solutions.
- Independently execute and review others exploratory data analysis to ensure data quality and relational characteristics
- Design, develop, and review real-time/bulk data pipelines from a variety of sources (streaming data, APIs, data warehouse, messages, images, video, etc.)
- Develop, review, and secure documentation of Data Lineage and Data Dictionaries to create a broad awareness of the enterprise data model and its applications
- Actively champion and apply best practices within DataOps (Version Control, P.R. Based Development, Schema Change Control, CI/CD, Deployment Automation, Test Automation, Shift left on Security, Loosely Coupled Architectures, Monitoring, Proactive Notifications)
- Coordinate with other teams to design optimal patterns for data ingest, transformation, and egress as well as lead and coordinate data quality initiatives and troubleshooting
- Guide problem solving sessions, ensuring alignment to North Star. Provide mentorship and coaching to junior team members.
- Proactively adapt team makeup to increase project velocity and solution quality.
- Perform other duties as requested.
- This position requires domestic travel including air travel. If you are hired, you will be required to submit proof that you are fully vaccinated against COVID-19 in order to travel by air, unless the company has granted a medical or religious accommodation.
- Bachelor’s degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or closely related discipline and eight (8) years of relevant work experience including five (5) years of project management/leadership experience;
- Master’s in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or closely related discipline and six (6) years of relevant work experience including three (3) years of project management/leadership experience;
- Ph.D. in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or closely related discipline and four (4) years of relevant work experience including three (3) years of project management/leadership experience
- Expert practitioner of Python development with experience designing high quality, production Python codebases
- Expert in data engineering, software engineering, and ML systems architecture
- Experience applying software development best practices in data engineering projects, including Version Control, P.R. Based Development, Schema Change Control, CI/CD, Deployment Automation, Test Driven Development/Test Automation, Shift left on Security, Loosely Coupled Architectures, Monitoring, Proactive Notifications using Python and SQL
- Data science experience wrangling data, model selection, model training, modeling validation, e.g., Operational Readiness Evaluator and Model Development and Assessment Framework, and deployment at scale
- Experience with Agile and DevOps software development principles/methodologies, keep team focus on deliver business value
- Experience leading and developing teams
- Experience with at least one modern Machine Learning framework such as TensorFlow, Pytorch, Keras, etc.
- Understanding of Machine Learning fundamentals
- Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking to large audiences
- Working knowledge of Azure Stream Architectures, DBT, Schema Change tools, Data Dictionary tools, Azure Machine Learning Environment, GIS Data
- Working knowledge of Software Engineering and Object Orient Programming Principles
- Working knowledge of Distributed Parallel Processing Environments such as Spark or Snowflake
- Working knowledge of Edge Analytics, embedded systems, or computer vision.
- Working knowledge of problem solving/root cause analysis on Production workloads
- Experience working in Data Science Product Teams, managing Design, Implementation of data projects that utilize big data, advanced analytics and machine learning technologies.
- Working knowledge of Agile, Scrum, and Kanban
- Working knowledge of workflow orchestration using tools such as Airflow, Prefect, Dagster, or similar tooling
- Experience building OR implementing a feature store
- Working knowledge with CI/CD and automation tools like Jenkins or Azure DevOps
- Experience with containerization tools such as Docker
- Our client promotes a drug/alcohol free work environment through the use of mandatory pre-employment drug testing and on-going random drug testing.