Who we are: Founded in 2012, automotiveMastermind is a leading provider of predictive analytics and marketing automation solutions for the automotive industry and believes that technology can transform data, revealing key customer insights to accurately predict automotive sales. Through its proprietary automated sales and marketing platform, Mastermind, the company empowers dealers to close more deals by predicting future buyers and consistently marketing to them. automotiveMastermind is headquartered in New York City. For more information, visit automotivemastermind.com.
At automotiveMastermind, we thrive on high energy at high speed. We're an organization in hyper-growth mode and have a fast-paced culture to match. Our highly engaged teams feel passionately about both our product and our people. This passion is what continues to motivate and challenge our teams to be best-in-class. Our cultural values of "Drive" and "Help" have been at the core of what we do, and how we have built our culture through the years. This cultural framework inspires a passion for success while collaborating to win.
What we do: Through our proprietary automated sales and marketing platform, Mastermind, we empower dealers to close more deals by predicting future buyers and consistently marketing to them. In short, we help automotive dealerships generate success in their loyalty, service, and conquest portfolios through a combination of turnkey predictive analytics, proactive marketing, and dedicated consultative services.
JOB DESCRIPTION SUMMARY:
A Successful Senior Data Engineer will:
Use the latest technology to build data integrations with internal and external partners
Build and expand our data platform
Develop applications that run on a Google Cloud-based infrastructure
6+ years of experience in Big Data and Data Engineering.
Strong knowledge of advanced SQL and data warehousing concepts, including BigQuery.
Have strong programming skills in SQL, Python/PySpark etc.
Experience in the design and development of data pipelines, ETL/ELT processes.
Experience in one of the public cloud providers - GCP, Azure, AWS.
Experience with relational SQL and NoSQL databases, including Postgres and MongoDB.
Experience with workflow management tools: Airflow, AWS data pipeline, Google Cloud Composer, etc.
Comfortable using Azure DevOps or similar CI/CD tools, Git
Building Docker images and deploying them to production. Integrate Docker container orchestration framework using Kubernetes by creating pods, config maps, deployments using terraform.
Strong problem solving and communication skills.
Bachelor's or an advanced degree in Computer Science or related engineering discipline.
Optionally have experience with C#, .NET core, and microservice
Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is $77,400 to $160,000. Final base salary for this role will be based on the individual's geographical location as well as experience and qualifications for the role.
In addition to base compensation, this role is eligible for an annual incentive plan.
This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, visit link https://spgbenefits.com/benefit-summaries/us
Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law.