Senior DataOps Engineer

Scout Motors•Charlotte, NC

2d•$140,000 - $170,000•Hybrid

About The Position

Here at Scout Motors, we're carrying forward the heritage of one of the most iconic American vehicles in history. A vehicle dating back to 1960. One that forged the path for future generations of rugged SUVs and trucks and will do so once again. But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work. The Scout brand is all about respect. Respect for the past and the future by taking an iconic American brand that hasn’t been around for a while, electrifying it, digitizing it, and loading it with American innovation. Respect for communities by creating a company that stands for its people and its customers. Respect for both work and play, with vehicles that are equally at home at a camp site, a job site, or on a Tuesday commute. And respect for our customers by developing two powertrains that meet their requirements — an all-electric powertrain as well as the Harvester™ range extender powertrain which includes a built-in gas-powered generator with an estimated 500 miles of combined range. At Scout Motors, we empower our talented, inclusive, and entrepreneurial teams to innovate. What makes a Scout employee? Someone who is a visionary and a leader, who seeks new paths and shares lessons learned. A knowledgeable doer who collaborates across the company to build better. A go-getter with unrivaled passion. Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now! About the Team The Data Platform Team at Scout is dedicated to unlocking the full potential of data by building a secure, scalable, and distributed platform that enables real-time insights, drives informed decision-making, and fosters innovation across the organization. Our mission is to empower teams with actionable intelligence by streamlining data sharing, ensuring regulatory compliance, maintaining data integrity, and optimizing costs at every level. This role is focused on building foundation for deploying AI-enabled use cases across company operations.

Requirements

Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive environment.
Experience with streaming and event-based architecture.
Experience implementing data lakehouse solutions using Databricks.
Experience with infrastructure as code (Terraform).
Proficient in building data pipelines using languages such as Python and SQL.
Experience with AWS based data services such as Glue, Kinesis, Firehose or other comparable services.
Experience with Structured, unstructured and time series databases.
Solid understanding of cloud data storage solutions such as RDS, DynamoDB, DocumentDB, Mongo, Cassandra, Influx.
Several years of experience working with cloud platforms such as AWS and Azure.
Proven ability to develop and deploy scalable ML models.
Hands-on experience in designing, training, and deploying ML models
Strong ability to extract actionable insights using ML techniques
Ability to leverage ML algorithms for forecasting trends and decision-making
Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options.

Responsibilities

Contribute to the design, implementation, and maintenance of the overall cloud infrastructure data platform using modern IaC (Infrastructure as Code) practices.
Work closely with software development and systems teams to build Data Integration solutions.
Design and build Data models using tools such as Lucid, Talend, Erwin, MySQL workbench.
Define and enhance enterprise data model to reflect relationships and dependencies.
Review application data systems to ensure adherence to data governance policies.
Design and build ETL (Python), ELT(Python) infrastructure, automation, and solutions to transform data as required.
Design and Implement BI dashboards to visualize Trends and Forecasts.
Design and implement data infrastructure components, ensuring high availability, reliability, scalability, and performance.
Design, train and deploy ML models
Implement monitoring solutions to proactively identify and address potential issues.
Collaborate with security teams to ensure the data platform meets industry standards and compliance requirements.
Collaborate with cross-functional teams, including product managers, developers, and business partners to ensure robust and reliable systems.

Benefits

Competitive insurance including:
Medical, dental, vision and income protection plans
401(k) program with:
An employer match and immediate vesting
Generous Paid Time Off including:
20 days planned PTO, as accrued
40 hours of unplanned PTO and 14 company or floating holidays, annually
Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave

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