Arity - Data Analytics Engineer - Lead Cons

Key Skills

Continuous Integration & Continuous Delivery - CI/CD, Data Analytics, Data science techniques, Docker, Kubernetes-K8s, Machine learning techniques, Pandas, PySpark, Python Programming, Scala Programming, SciPy, SPARK Programming

Job Description

The Team

Our Data Science team is fueled by a passion to impact the future of mobility. We love to find the meaning within the 100’s of billions of miles of driving data we collect each year. We push the boundaries of telematics and transportation by building data and machine learning solutions to power our groundbreaking products.

We are a team of data scientists, data engineers, and analysts that take full ownership of our data pipelines and feature generation and use AWS Managed Services as the basis of our technology stack. As a part of the team, in collaboration with product owners and other experts, your work will showcase your intelligence and creativity as you solve real problems that will improve transportation and even save lives. Personally, we think that’s game-changing stuff. 

The Role

We are seeking a highly motivated Senior Data Analytics Engineer to join our Analytics Data Engineering team inside of Data Science. You’ll help us continue to build out an analytics data ecosystem that organizes our data for research, merges disparate sources together, and ensures data privacy best practices. You will work with a team of data engineers dedicated to creating the best telematics data and insights platform in the market.

You will help us build the next generation of deep mobility insights by extracting relevant behavioral and geospatial patterns from users’ trip data. Your team will help us find new sources of telematics data and figure out how to ingest, normalize, and process it at a scale of over 500 trips per second with full system observability.

Responsibilities

• Build pipelines that source data from operational systems and then process and organize it to optimize for R&D efforts across Arity 
• Apply appropriate methodologies for the problem using a variety of tool sets and writing code in Scala or Python.
• Create highly reusable and reliable code and leverage CI/CD principles to create robust data applications 
• Explore data across the company and work cross-functionally to find opportunities for new data sets that can support our products 
• Ensure projects have appropriate measures of success that support data-driven development 
• Create reusable validations of data pipelines and guide the implementation of monitoring 
• Support a culture of reproducibility via peer review, code review, and documentation 
• Drive continuous improvement of data science and data engineering practices to create world-class capabilities 
• Influence analytics strategy and roadmap with your combination of data engineering expertise and domain experience 
• Build the Arity technical brand by engaging in conferences, meetups, blogs, and other external public engagements 
• Drive recruiting by building relationships in the industry and supporting our interviewing efforts 

Qualifications

• Bachelor’s degree in Geospatial Science, Mathematics, Statistics, Physics, Computer Science, Engineering, or related quantitative field. A Master's degree is preferred. 
• At least five years of industry experience in data engineering or related roles such as Software Engineering
• Remote employment experience
• Experience with several of EMR, Spark, Kinesis, Athena, and Airflow
• Respected by peers for technical prowess in Scala. Python is a plus
• Ability to translate business problems into well-defined data and analytics problems with quantitative success measures 
• Experience driving end-to-end data engineering projects to generate measurable business value, including ideation, development, deployment, and maintenance & monitoring 
• Ability to envision and articulate radical change through highly innovative thought leadership 
• Inspires, mentors, and enables team to be bold and deliver high quality work 
• Comfortable in a fast-paced environment with high ambiguity; inspires others to embrace these conditions 

Nice to Have

• Geospatial, sensor, or telematics experience is quite valuable, but not required 
• Docker, Kubernetes, CI/CD, Terraform
• Data Science and machine learning (Pandas, Scikit learn) 
• You write code to transform data between data models and formats, preferably in Scala / Spark, Python or PySpark.
• Experience moving trained machine learning models

Compensation offered for this role is $130,400.00-$179,675.00 per year and is based on experience and qualifications.