As a Data Engineer, you will be responsible for building and maintaining the infrastructure that supports data collection, processing, and storage. Reporting to the Lead Data Engineer or Principal Data Engineering, you will work closely with data scientists, analysts, and other stakeholders to ensure that data systems are reliable, scalable, and secure. Your work will be crucial in enabling data-driven decision-making across the organization.
The Data Engineer is a key technical role focused on developing and optimizing the company's data infrastructure. This role involves designing and implementing data pipelines, ensuring data quality, and collaborating with cross-functional teams to support various data initiatives. The ideal candidate will possess strong technical skills in data engineering, experience with data architectures, and a passion for working with data.
Key Responsibilities:
- Design and construct highly scalable data pipelines with a focus on machine learning models and analytics.
- Collaborate with data scientists and ML engineers to ensure data accessibility, consistency, and reliability for ongoing projects.
- Develop and maintain APIs for data access and manipulation, and integrate with external data services as needed.
- Manage and optimize data storage solutions, including relational and unstructured data.
- Implement processes to monitor data quality and ensure production data is accurate and available for key stakeholders.
- Ensure compliance with data security and privacy policies.
- Maintain clear and up-to-date documentation, including data dictionaries and architectural diagrams.
Required Skills and Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or equivalent work experience.
- 3+ years of experience in a Data Engineering role.
- Proficiency in programming languages such as Python, Java, and Scala for managing large scale data.
- Hands-on experience with big data technologies like Hadoop, Spark, and Flink.
- Familiarity with machine learning frameworks such as TensorFlow or PyTorch.
- Strong understanding of data warehousing concepts, ETL processes, and data modeling.
- Experience with API development and integration with data services.
- Experience with cloud platforms like Azure.
- Knowledge in DevOps, CI/CD methods, and containerization technologies like Docker or Kubernetes.
- Experience with real-time/streaming data processing.
What We Look For:
We seek a performance-driven and inquisitive individual who can adapt to ambiguity. You should be eager to explore collaboration opportunities with stakeholders and aspire to create unique, customer-centric solutions. A bias for action and a passion for new frontiers in the AI space is central to our community.
Work Culture and Benefits:
- Open, diverse, and inclusive environment with a global vision encouraging personal growth and innovative solutions.
- Opportunities for learning, development, and growth through structured training programs and high-tech projects.
- Hybrid work policy to balance office and home work.
- Competitive remuneration package with perks including healthcare, education support, and leave benefits.
Language Requirements:
- Proficiency in English is required.
If you meet the above criteria, we encourage you to apply.
