About Us

Mercedes-Benz is USA is responsible for the sales, marketing and service of all Mercedes-Benz and Maybach products in the United States. In our people, you will find tremendous commitment to our corporate values. Our products and employees reflect this dedication. We are looking for diverse top-notch individuals to join the Mercedes-Benz Team and uphold these hallmarks.

Job Overview 

The Data Ops Engineer is responsible for day-to-day technical development and delivery of data pipelines into Data Platforms @ MBUSA. You will ensure delivery of solutions based on the backbone of good architecture, best data engineering practices around operational efficiencies, security, reliability, performance and cost optimization. 

Responsibilities

• Design, build and optimize data engineering pipelines to extract data from different sources and applications and feed into cloud data platform
• Work closely with MBUSA Data & Insights team in building, testing and productionising data extraction, transformation and reporting solutions within data platform
• Code, test, and document new or modified data models and ETL/ELT tools to create robust and scalable data assets for reporting and analytics
• Peer review code and promote dev ops culture within data team
• Develop ETL/ELT pipelines on Azure Data Platform using ADF, Databricks or Python to load data across multiple sources into the datalake, warehouse and data marts
• Build and maintain the CI/CD pipelines to improve developer productivity, agility and code quality
• Be in charge of Data Ingestion Process for Data needed for Data solutions and projects (1st, 2nd and 3rd party data) including structural, semi-structural and nonstructural data
• Enhance the quality of data following the guidelines provided by the Data Quality Frame work and maintain the cataloging of data and dictionary
• Maintain platform performing regular tasks such as user management and audit, resource utilization, alerts monitoring, code reviews
• Have a good understanding of data platform best practices to achieve economies of scale, cost reduction and efficiencies

To be successful in this role, you have to be an experienced Data Ops Engineer with demonstrated knowledge and experience within data delivery, ETL/ELT, data management, solution design and delivery. 

Qualifications

Education: University degree or above in Computer Engineering, Computer Science or equivalent.

Experience: 

Essential:

•    A minimum of 3 years work experience in Data Engineering   
•    3+ years of hands on experience in building ETL/ELT for large scale data pipelines
•    3+ years of experience with solution architecture, data ingestion, query optimization, data segregation, ETL, ELT, CI/CD framework
•    1+ years experience on SQL Server or Azure Synapse data warehouses 
•    Hands on experience in data processing (using Spark, Python) for cloud data platforms, scheduling and monitoring of ETL/ELT jobs in Azure 
•    Maintain platform performing regular tasks such as user management and audit, resource utilization, alerts monitoring & code reviews
•    Experience building frameworks and tools (mostly Spark, Scala, Python) to process data and generate modelling data more efficiently

Desirable but not Essential:

•    1+ years' experience with data visualization tools such as Power BI
•    1+ years’ experience on Azure stack (SQL Warehouse, Azure Functions, Log Analytics etc)
•    1+ years’ experience working on Agile delivery framework including Scrum, Kanban 
•    A background in the automotive domain

Additional Information:

•    Must be able to work flexible hours/work schedule
•    Travel domestically and internationally as needed
•    Work Holidays when required
•    Work weekends when required
•    A self-starter and self-motivated

EEO Statement

Mercedes-Benz USA is committed to fostering an inclusive environment that appreciates and leverages the diversity of our team. We provide equal employment opportunity (EEO) to all qualified applicants and employees without regard to race, color, ethnicity, gender, age, national origin, religion, marital status, veteran status, physical or other disability, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local law.