EHM_JD_Data_Engineer_4+

• Responsible and self-driven work in the field of data engineering.

• Design, develop, and maintain data pipelines and ETL processes to ingest, process, transform and store large volumes of data from diverse sources.
• Collaborate with the business stakeholders to understand their data requirements and provide data-driven solutions and insights for decision making.
• Optimize and tune data pipelines and database performance for scalability, efficiency, and reliability.
• Implement and maintain data warehouses, data lakes, and other data storage solutions for efficient data retrieval and analysis.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Create data visualizations and reports to communicate findings effectively to technical and non-technical audiences.
• Stay updated with the latest data engineering, tools, and best practices.
• Interest in Data (Analysis, Schema, Validation, Visualization)
• Should be able to handle both big data and small data.

• Proven experience as a Data Engineer, showcasing expertise in both domains.

• Proficiency in programming languages such as Python with proper coding standards.
• Strong knowledge in PySpark, IMPALA, HIVE & Tableau.
• Strong experience with SQL and relational databases (e.g., PostgreSQL, MySQL, etc.).
• Familiarity with NoSQL databases (e.g., MongoDB, Cassandra) is a plus.
• Knowledge of data modeling, data warehousing, and data architecture.
• Experience with big data processing frameworks (e.g., Hadoop, Spark).
• In-depth knowledge of orchestration and scheduling jobs for data engineering pipelines with Apache Airflow.
• Experience with Cloud-based data solutions (e.g., AWS, Azure, GCP) is advantageous.
• Experience with JIRA, GIT & Bitbucket.
• Excellent problem-solving and analytical skills.
• Strong communication and presentation skills.
• Ability to work independently and collaboratively in a team environment.

Bosch