The ideal candidate will have strong experience in data engineering, cloud technologies, and software development, with a passion for building reliable, scalable, and secure data solutions.Required technical expertise includes:-
Strong proficiency in SQL, Python, and Java.
- Hands-on experience designing, developing, and deploying cloud-based data pipelines using Google Cloud Platform (GCP), including BigQuery, Dataflow, and Dataproc.
- Experience with relational databases such as PostgreSQL and MySQL, as well as NoSQL and columnar databases.
- Understanding of Service-Oriented Architecture (SOA) and microservices-based solutions.
- Knowledge of data governance, security controls, encryption, and data masking techniques.
- Experience implementing CI/CD pipelines and Infrastructure as Code (IaC) using tools such as Terraform and Tekton.
- Ability to monitor, troubleshoot, and optimize cloud workloads for performance, scalability, and cost efficiency.
- Strong analytical, problem-solving, and communication skills.
- Data Pipeline Architect & Builder: Spearhead the design, development, and maintenance of scalable data ingestion and curation pipelines from diverse sources. Ensure data is standardized, high-quality, and optimized for analytical use. Leverage cutting-edge tools and technologies, including Python, SQL, and DBT/Dataform, to build robust and efficient data pipelines.
- End-to-End Integration Expert: Utilize your full-stack skills to contribute to seamless end-to-end development, ensuring smooth and reliable data flow from source to insight.
- GCP Data Solutions Leader: Leverage your deep expertise in GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that not meet but exceed business needs and expectations.
- Data Governance & Security Champion: Implement and manage robust data governance policies, access controls, and security best practices, fully utilizing GCP's native security features to protect sensitive data.
- Data Workflow Orchestrator: Employ Astronomer and Terraform for efficient data workflow management and cloud infrastructure provisioning, championing best practices in Infrastructure as Code (IaC).
- Performance Optimization Driver: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions, ensuring optimal resource utilization and cost-effectiveness.
- Collaborative Innovator: Collaborate effectively with data architects, application architects, service owners, and cross-functional teams to define and promote best practices, design patterns, and frameworks for cloud data engineering.
- Automation & Reliability Advocate: Proactively automate data platform processes to enhance reliability, improve data quality, minimize manual intervention, and drive operational efficiency.
- Effective Communicator: Clearly and transparently communicate complex technical decisions to both technical and non-technical stakeholders, fostering understanding and alignment.
- Continuous Learner: Stay ahead of the curve by continuously learning about industry trends and emerging technologies, proactively identifying opportunities to improve our data platform and enhance our capabilities.
- Business Impact Translator: Translate complex business requirements into optimized data asset designs and efficient code, ensuring that our data solutions directly contribute to business goals.
- Documentation & Knowledge Sharer: Develop comprehensive documentation for data engineering processes, promoting knowledge sharing, facilitating collaboration, and ensuring long-term system maintainability.
Required
- Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, Engineering, or a related field, or equivalent practical experience.
5 to 7 years of experience in Data Engineering or Software Engineering.
Strong English Skills
- Minimum 2 years of hands-on experience building and deploying cloud-based data platforms, preferably on Google Cloud Platform (GCP).
- Strong proficiency in SQL and Python.
- Experience with BigQuery, Dataflow, Dataproc, and cloud-based data processing technologies.
- Experience with Terraform, CI/CD pipelines, and automation frameworks.
- Knowledge of cloud security, data governance, and data quality best practices.
Preferred
- Experience with DBT, Dataform, or similar transformation frameworks.
- Experience with Apache Airflow or Astronomer.
- Experience designing microservices and API-based integrations.
- Exposure to FinOps practices and cloud cost optimization.
Ford of Mexico is committed to being an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, pregnancy, veteran status, or disability status.
Our focus is to build the best team. If you think you can bring value to Ford, love to collaborate, prioritize and aim to deliver excellence in everything you do, we encourage you to apply!
We thank all candidates for their interest, but those selected for an interview will be contacted.
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