As a Data Engineer at the company, 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.
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Responsibilities
Your key responsibilities include:
- Designing, constructing, installing, testing, and maintaining highly scalable data pipelines with a focus on machine learning models and analytics.
- Collaborating with data scientists, ML engineers, and stakeholders to ensure that data is accessible, consistent, and reliable for ongoing projects.
- Developing and maintaining APIs for data access and manipulation, and integrating with external data services as needed.
- Managing and optimizing data storage solutions, including relational databases and NoSQL databases, to support the requirements of machine learning models.
- Implementing processes to monitor data quality and ensure production data is always accurate and available for key stakeholders.
- Collaborating with ML engineers to assist in data-related technical issues and provide architectural guidance and solutions.
- Ensuring compliance with data security and privacy policies.
- Maintaining clear and up-to-date documentation including data dictionaries, metadata, and architectural diagrams.
Qualifications
To be successful in this role, you should have:
- A Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or equivalent work experience.
- 7+ years of experience in a Data Engineering role.
- Proficiency in SQL and programming languages like Python and Scala.
- 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, AWS, or GCP.
- Knowledge in DevOps, CI/CD methods, and Kubernetes.
What Working at the company Offers
- Culture: An open, diverse and inclusive environment that encourages personal growth and focuses on innovative solutions.
- Career: Outstanding learning, development & growth opportunities via structured training programs.
- Work-Life: A hybrid work policy to strike the perfect balance between office and home.
- Rewards: A competitive remuneration package with benefits including healthcare and education support.
