As a Senior Data Science Engineer, you will play a critical role in designing, developing, and maintaining our data infrastructure and pipelines. Your expertise will drive the effective collection, storage, processing, and analysis of large-scale data sets, enabling actionable insights and data-driven decision-making across the organization. You will collaborate with cross-functional teams, including software engineers, and product managers, to deliver scalable and high-performance data solutions that support our growing product needs.
Job Description In Breif -
- Design and Develop Data Solutions: Lead the end-to-end design and development of scalable, efficient, and reliable data pipelines and ETL workflows. Implement data integration processes from various sources to central data repositories.
- Data Modeling and Architecture: Design and optimize data models for both structured and unstructured data, ensuring efficient data storage and retrieval. Evaluate and propose appropriate database technologies and data storage solutions.
- Data Quality and Governance: Implement data quality checks and ensure data integrity across all data assets. Establish and maintain data governance practices to guarantee compliance with data security and privacy regulations.
- Performance Optimization: Continuously monitor and enhance the performance of data pipelines, databases, and data processing systems to achieve optimal efficiency and low latency.
- Big Data Technologies: Stay up-to-date with the latest trends and advancements in big data technologies, frameworks, and tools. Evaluate and introduce new technologies to improve data engineering processes.
- Collaboration and Leadership: Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and provide the necessary infrastructure and support. Mentor and guide junior data engineers to foster a high-performing data engineering team.
- Documentation and Best Practices: Maintain comprehensive documentation for all data processes, methodologies, and configurations. Promote and enforce best practices in data engineering across the organization.
- Troubleshooting and Support: Investigate and resolve data-related issues, including performance bottlenecks, data inconsistencies, and system failures.
Requirements
Requirements:
- Bachelor's or master's degree in computer science, Software Engineering, Data Science, or a related field.
- Proven experience as a Data Engineer or similar role, with at least [4] years of hands-on experience in building large-scale data pipelines and data integration solutions.
- Proficient in programming languages such as Python, Java, Scala, or similar, with a focus on data manipulation and processing.
- Expertise in working with big data technologies like Bigquery, Redshift, Snowflak, Spark, Kafka, or similar distributed computing frameworks.
- Strong experience with SQL and NoSQL databases, data warehousing, and data modeling techniques.
- In-depth knowledge of cloud platforms like AWS, Azure, or Google Cloud, and experience with cloud-based data storage and processing services.
- Familiarity with data security and privacy standards, as well as data governance practices.
- Excellent problem-solving skills and the ability to analyze complex data-related issues.
- Strong communication skills to collaborate effectively with cross-functional teams and stakeholders.
- Experience with containerization technologies (e.g., Docker, Kubernetes) is a plus.
- Certifications in relevant data engineering or cloud technologies are advantageous.
