Data Engineer

Key Skills

Apache Cassandra, Apache Flink, Apache Hadoop, Apache Kafka, API, AWS, Azure, Big Data Technology, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Database, DevOps, Docker, Elasticsearch, Google Cloud Platform (GCP), GraphQL, HBase, Java Programming, Kubernetes-K8s, Large scale data processing, Machine learning techniques, MongoDB, MySQL, NoSQL, OpenAPI, PostgreSQL, Python Programming, RabbitMQ, REDIS, RESTful, Scala Programming, SPARK Programming, SQL

Job Description

Key Responsibilities

Data Pipeline Architecture and Development

• Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics.

Data Integration

• Work closely with data scientists, ML engineers, and stakeholders to ensure that data is accessible, consistent, and reliable for ongoing projects.

API and Data Services

• Develop and maintain APIs for data access and manipulation, and integrate with external data services as needed.

Data Storage

• Manage and optimize data storage solutions, including relational databases, Search Engines like Elasticsearch and NoSQL databases, to support the requirements of machine learning models.
• Understand data engines and structure to effectively design solutions for transactional, analytics, and search purposes.

Data Quality and Governance

• Implement processes to monitor data quality and ensure production data is always accurate and available for key stakeholders.

Collaboration and Support

• Collaborate with ML engineers to assist in data-related technical issues and provide architectural guidance and solutions.

Security and Compliance

• Ensure compliance with data security and privacy policies.

Documentation

• Maintain clear and up-to-date documentation including data dictionaries, metadata, and architectural diagrams.

Qualifications

To qualify you must have,

• 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 SQL and programming languages like Python, Java, and Scala.
• Hands-on experience with big data technologies like Hadoop, Spark and Flink.
• Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar.
• 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 AWS, GCP.
• Knowledge in DevOps, CI/CD methods, and containerization technologies like Docker or Kubernetes.
• Experience with real-time data processing.

Technical stack

• Programming Languages: Python, Java, Scala, SQL, Bash
• Big Data Technologies: Hadoop, Spark, Flink
• Databases: MySQL, PostgreSQL, MongoDB, Cassandra, HBase, Redis
• Cloud Platforms: Azure
• API Development: RESTful APIs, GraphQL, OpenAPI
• Data Services: Kafka, RabbitMQ
• Containers: Docker, Kubernetes