Data Engineer

Senior Data Engineer

Your role

• Designing and implementing scalable data pipelines to collect, process, transform, and store large volumes of structured and unstructured data.
• Developing efficient ETL (Extract, Transform, Load) processes to ensure the availability of clean and accurate data for analysis.
• Building and maintaining data warehouses or data lakes to enable easy access to structured datasets for reporting and analytics purposes.
• Collaborating with cross-functional teams to identify opportunities for improving data quality, reliability, performance, and efficiency.
• Implementing appropriate security measures to protect sensitive data from unauthorized access or breaches.
• Monitoring system performance, identifying bottlenecks or issues, and implementing optimizations to ensure high availability and scalability.
• Conducting thorough testing of developed solutions to ensure they meet functional requirements and performance expectations.
• Mentoring junior team members by providing guidance on best practices in software development, database design, and data engineering techniques.
• Staying up-to-date with emerging technologies in the field of big data processing, cloud computing, distributed systems, etc., and evaluating their potential applications in the organization's context.
• Collaborating with stakeholders to understand their business needs and translating them into technical requirements.

To succeed in this role

• Bachelor's or Master's degree in Computer Science, Engineering or a related field.
• Proven experience as a Data Engineer or similar role with a focus on building scalable data processing systems.
• Strong programming skills in languages like Python/Java/Scala along with proficiency in SQL for querying databases.
• Experience working with big data technologies such as Hadoop ecosystem (HDFS, MapReduce), Apache Spark/PySpark for distributed computing.
• Proficiency in working with relational databases (e.g., MySQL) as well as NoSQL databases (e.g., MongoDB).
• Familiarity with cloud platforms like GCP/AWS/Azure for deploying scalable infrastructure using services like S3, EC2 instances etc.
• Knowledge of containerization technologies like Docker/Kubernetes is desirable but not mandatory.
• Strong problem-solving skills with an ability to analyze complex datasets efficiently.
• Excellent communication skills to effectively collaborate with cross-functional teams.
• Candidate should have a strong understanding of data platforms, including architecture, components, and functionalities.
• Candidate should be proficient in data integration, storage, processing, analytics, and visualization technologies.
• Knowledge of programming languages like SQL, Python, or R is also beneficial.