Senior Software Engineer - Data Engineer

Devsinc is seeking a highly skilled Senior Software Engineer with a focus on Data Engineering and Data Science to join our innovative team. This role demands an individual capable of bridging the gap between software engineering and data science, leveraging advanced algorithms and extensive data sets to drive impactful insights and solutions.

Key Responsibilities:

• Design and develop data pipelines and architectures to effectively process and analyze large volumes of structured and unstructured data.
• Collaborate with data scientists and analysts to implement data models and algorithms that enable predictive analytics and machine learning.
• Optimize and maintain existing data systems to ensure efficiency, performance, and scalability.
• Conduct data analysis to extract meaningful insights and communicate findings to stakeholders.
• Implement best practices for data governance, security, and compliance.
• Mentor junior engineers and contribute to the continuous improvement of engineering processes and methodologies.
• Stay up-to-date with emerging trends in data engineering and data science to innovate solutions to complex problems.

• Bachelor's or Master’s degree in Computer Science, Data Science, or a related field.
• 3+ years of experience in software engineering with a strong emphasis on data engineering and data science projects.
• Extensive experience with ETL processes, data warehousing, and big data technologies (e.g., Hadoop, Spark).
• Strong proficiency in programming languages such as Python, R, or Scala.
• Proficiency in SQL and familiarity with NoSQL databases (e.g., MongoDB, Cassandra).
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with cloud platforms like AWS, Azure, or GCP, particularly in data processing and storage services.
• Familiarity with data visualization tools and techniques.
• Excellent analytical and problem-solving skills, with the ability to work with complex datasets and extract actionable insights.
• Strong communication skills, capable of translating technical concepts to non-technical audiences.
• Ability to lead projects and coordinate with cross-functional teams in an agile environment.
• Willingness to continuously learn and adapt to new challenges in the data landscape.