Data Engineer
Role details
Job location
Tech stack
Job description
We are seeking a talented Data Engineer with hands-on experience in building scalable data pipelines and modern cloud-based data platforms. The ideal candidate will have experience working with Python and big data technologies such as Apache Airflow, Apache Spark, and Apache Beam, along with strong knowledge of SQL and data warehousing concepts. In this role, you will design and develop cloud-native data pipelines on Google Cloud, enabling reliable data processing and integration of machine learning models. You will work closely with data scientists, engineers, and cross-functional teams to build and expand our enterprise data platform while ensuring high performance, scalability, and reliability of data solutions. The position requires strong collaboration skills, experience working in agile development environments, and familiarity with CI/CD practices, cloud infrastructure, and modern data engineering tools. Responsibilities
- Use the latest technology to build data pipelines and integrate machine learning models
- Build and expand our data platform
- Develop applications that run on a Google Cloud-based infrastructure.
Requirements
- Experience in Big Data and Data Engineering, building enterprise-level applications in a public cloud, preferably Google Cloud
- Experience building cloud-native data pipelines using Python, Apache Airflow, Apache Spark, and Apache Beam.
- Working knowledge of SQL and data warehousing concepts, including PostgreSQL and BigQuery.
- Optionally, knowledge of Mongo and AlloyDB is a plus.
- Comfortable using Azure DevOps or similar CI/CD tools, Git.
- Experience with TDD, agile software development processes, and collaborating in multi-functional agile teams.
- Communicate effectively with technical teams and non-technical stakeholders.
- Bachelor''''s degree in Computer Science or related engineering discipline, or equivalent combination of education and experience.
- Optionally, experience building Docker images and deploying them to a Production environment. Integrate Docker container orchestration framework using Kubernetes by creating pods, config Maps, and deployments using Terraform.
- Optionally, experience with C#, .NET core, and microservices