Information Technology
Other
McKinsey & Company
Overview
Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.
Your Impact
As a Backend Engineer with Data Engineering expertise, you will be responsible for building and maintaining the server-side logic of web applications, ensuring they are scalable, efficient, and secure.
You will collaborate closely with cross-functional teams, including front-end developers, product managers, and database administrators, to deliver high-quality solutions that meet business requirements.
In addition to traditional backend responsibilities, you will play a critical role in designing and managing robust data pipelines, ensuring efficient data storage and retrieval, and enabling advanced analytics capabilities. Your expertise will help shape the architecture, enhance system performance, and ensure seamless integration of backend systems and data platforms.
Your Growth
We are looking for talented and ambitious individuals who thrive on learning, problem-solving, and driving innovation.
Your qualifications and skills
- Collaborate with cross-functional teams to understand software requirements and design scalable backend solutions
- Develop server-side logic, RESTful APIs, and web services using languages such as Python
- Design and implement data processing workflows and ETL pipelines for structured and unstructured data
- Integrate data from various sources (APIs, databases, streaming services) for analytical and operational use
- Design and optimize database schemas for efficient data storage and retrieval
- Database Proficiency: (Relational Databases: Strong knowledge of SQL and experience with MySQL or PostgreSQL, including query optimization; NoSQL Databases: Experience with MongoDB, Cassandra, or DynamoDB for flexible and scalable data storage; Graph Databases: Ideal knowledge of Neo4j for managing complex relationships and interconnected data)
- Design and maintain data pipelines using tools like Apache Airflow or Luigi
- Implement data modeling, data warehousing, and ETL processes to support analytics and reporting
- Optimize and manage big data solutions using technologies like Apache Spark or Flink for distributed data processing
- Monitor and analyze system performance to identify bottlenecks and optimize server-side infrastructure
- Optimize data storage and query performance for both SQL and NoSQL databases
- Improve the efficiency of data processing pipelines and big data workflows
- Stay updated on emerging technologies to improve scalability and efficiency
- Work closely with front-end developers to integrate APIs and backend components
- Collaborate with data scientists and analysts to understand data requirements and deliver relevant solutions
- Perform code reviews and provide feedback to ensure adherence to quality standards
- Proficiency in building RESTful APIs and microservices architectures
- Proficiency in version control tools like Git
- Knowledge of CI/CD pipelines and DevOps practices
- Experience with containerization and orchestration tools like Docker and Kubernetes
- Familiarity with cloud platforms (AWS, Azure, or Google Cloud) for scalable infrastructure
- Self learning attitude is MUST HAVE
- Strong problem-solving and analytical skills
- Excellent communication and collaboration skills for working with cross-functional teams
- Adaptability to new technologies and a fast-paced work environment
- Ability to translate complex technical requirements into clear, actionable solutions
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