Bangalore, Karnataka, India
Information Technology
Full-Time
Prodapt
Overview
Overview
The Data Analytics Engineer is responsible for designing, building, and maintaining data pipelines and models that facilitate data analysis. This role combines technical expertise in data engineering with analytical skills to support business decision-making processes.
Responsibilities
Data Modeling and Transformation
The Data Analytics Engineer is responsible for designing, building, and maintaining data pipelines and models that facilitate data analysis. This role combines technical expertise in data engineering with analytical skills to support business decision-making processes.
Responsibilities
Data Modeling and Transformation
- Develop and implement data models to organize and structure raw data into clean, usable datasets.
- Ensure the accuracy and reliability of data through rigorous validation and testing processes.
- Design and build automated data pipelines to extract, transform, and load (ETL) data from various sources into data warehouses.
- Optimize data workflows for efficiency and scalability, ensuring seamless integration of new data sources.
- Work closely with data scientists, analysts, and business stakeholders to gather requirements and understand analytical needs.
- Communicate complex technical concepts to non-technical stakeholders effectively.
- Maintain comprehensive documentation of data processes, models, and workflows to ensure transparency and reproducibility.
- Create user-friendly guides for accessing and utilizing datasets.
- Apply software engineering best practices, including version control, code reviews, and continuous integration/continuous delivery (CI/CD) methodologies.
- Stay updated on industry trends and emerging technologies to enhance data analytics capabilities.
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
- Proven experience in a data analytics or engineering role, with a strong focus on data modeling and pipeline development.
- Proficiency in SQL for querying databases and manipulating datasets.
- Familiarity with programming languages such as Python or R for data analysis and visualization.
- Strong understanding of data analysis principles and techniques.
- Experience with cloud platforms (e.g., AWS, Azure) and data warehousing solutions.
- Knowledge of business intelligence (BI) tools for visualizing and reporting data findings.
- Excellent problem-solving skills with attention to detail.
- Strong communication skills for effective collaboration across teams.
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