Senior Data Science Engineer

About the job

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 brief - • 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: • 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, Snowflake, 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.

Requirements

• Data Engineering
• Python
• SQL
• NoSQL
• Cloud Platforms

Qualifications

• Bachelor's or master’s degree in computer science
• Software Engineering
• Data Science
• or a related field.

Preferred Technologies

• Data Engineering
• Python
• SQL
• NoSQL
• Cloud Platforms