Data Engineer

bayer

Bengaluru, India 5 Years Exp Posted 2h ago

Data Analysis and Synthesis

Conduct data profiling and analyze source systems to ensure data quality.
Present clear insights and findings to colleagues to facilitate effective data usage.

Data Development Process

Data Integration Design

Select and implement appropriate technologies to create resilient, scalable, and future-proof data solutions and integration pipelines.

Data Modelling

Develop relevant data models across various subject areas and articulate their purposes.
Understand and apply industry-recognized data modeling patterns and standards.
Compare and align different data models to ensure consistency.

Metadata Management

Design and manage an effective metadata repository, and recommend changes to existing repositories.
Familiarize yourself with various tools for managing metadata.
Provide guidance and support to less experienced team members.

Problem Resolution

Address issues in databases, data processes, and data products as they arise.
Monitor services, identify trends, and initiate actions to resolve problems.
Determine appropriate remedies and assist with their implementation and preventive measures.

Programming and Build

Utilize established standards and tools to design, code, test, and document moderate-to-complex programs and scripts based on specifications.
Collaborate with team members to review specifications and ensure alignment.

Technical Understanding

Grasp core technical concepts related to data engineering and apply them with guidance.

Testing

Review requirements and specifications, and define test conditions.
Identify issues and risks associated with work, and analyze test activities and results.

WHO YOU ARE:

Required:

Bachelor’s degree in Computer Science, Data Science, or a related field.
5+ years of experience in data engineering or related roles, with a solid understanding of data integration and modelling.
Proficiency in programming languages such as Python, SQL, and experience with data processing frameworks (e.g., Apache Spark, Hadoop).
Familiarity with data warehousing solutions and ETL (Extract, Transform, Load) processes.
Experience with cloud data platforms (e.g., AWS, Azure, Google Cloud) and data storage solutions (e.g., relational databases, NoSQL databases).
Strong analytical skills and the ability to present complex data insights clearly to stakeholders.
- Excellent problem-solving abilities and a proactive approach to identifying and resolving issues.