As a Data Science Engineer, you will lead and contribute to data science projects from end to end starting with data collection and preprocessing, all the way through analysis, visualization, and strategic recommendation. You’ll collaborate with cross-functional teams, domain experts, and internal and external stakeholders to solve complex business challenges with innovative data-driven solutions.
This role blends technical expertise with strategic thinking, requiring a strong background in tools like SQL, PySpark, and Azure Databricks, as well as the ability to present complex information in a clear and compelling manner to both technical and non-technical audiences.
Key Responsibilities
- Work collaboratively within a team of data scientists and engineers on designing, developing, executing, and implementing innovative data science projects.
- Engage in all stages of the data lifecycle from data acquisition and cleansing to modeling and visualization—ensuring accuracy, consistency, and relevance of insights.
- Partner with cross-functional stakeholders to define business problems, determine appropriate data-driven methodologies, and deliver effective analytical solutions.
- Develop and automate robust data pipelines and scalable ETL workflows that drive real-time analytics and performance monitoring.
- Create intuitive and visually appealing dashboards and reports using tools like Power BI and Tableau to communicate insights and KPIs to diverse audiences.
- Conduct experiments and validations in collaboration with internal SMEs and external partners, contributing to the overall roadmap and strategy.
- Prepare clear and concise documentation, including technical specifications, analysis reports, and research presentations.
- Support the preparation of literature for publication, conference presentations, and patent filings, where applicable.
- Mentor and provide technical guidance to junior team members, fostering knowledge sharing and team development.
- Take ownership of moderately complex to high-complexity projects, ensuring timely delivery and adherence to best practices.
- Continuously explore new technologies, trends, and methodologies to improve analytical capabilities and promote innovation within the team.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Economics, or a related field. Equivalent work experience will also be considered.
- 5–8 years of experience in data engineering, data science, or a related analytical role. Candidates with an advanced degree should have at least 3–5 years of relevant experience.
- Hands-on experience with SQL, PySpark, and Azure Databricks in a production environment.
- Strong background in data preprocessing, data modeling, data quality assessment, and statistical analysis.
- Expertise in building interactive dashboards and data visualizations using tools like Power BI and Tableau.
- Solid understanding of cloud-based data engineering and analytics platforms, especially Microsoft Azure.
- Familiarity with source control tools such as Git, and working knowledge of Agile development methodologies.
- Excellent problem-solving skills and a strong ability to communicate complex technical concepts in simple, relatable terms.
Preferred Certifications
Skills & Competencies
- Technical Proficiency. Agile methodology, data warehousing, ETL processes, data management, statistics, business intelligence, and advanced analytics.
- Tools & Technologies. SQL, Python, PySpark, Azure Databricks, Power BI, Tableau, Git.
- Soft Skills. Strong communication, analytical thinking, adaptability, customer centricity, results orientation, and a commitment to continuous learning.
Why Join Us?
At our core, we believe in the power of data to transform business and drive progress. You’ll have the opportunity to work in a forward-thinking, agile environment where innovation is encouraged, and your work will have a direct impact on the organization’s strategic direction. We value continuous improvement, and we’ll support your professional growth through learning opportunities, mentorship, and exposure to cutting-edge technologies.