Netscribes - Data Engineer - ETL

2 weeks ago

Bengaluru, Karnataka, India NETSCRIBES DATA INSIGHTS PRIVATE LIMITED Full time

Responsibilities :

- Data Pipeline Development : Design, develop, and maintain robust and scalable data pipelines using Python and related technologies.

- ETL/ELT Processes : Implement and optimize ETL/ELT processes to extract, transform, and load data from various sources into data warehouses and data lakes.

- Data Modeling and Warehousing : Design and implement data models and data warehousing solutions to support analytical and reporting needs.

- Data Quality and Integrity : Ensure data quality and integrity through data validation, monitoring, and testing.

- Automation and Optimization : Automate data processing tasks and optimize data pipelines for performance and efficiency.

- Cloud Data Platforms : Utilize cloud data platforms (AWS, Azure, GCP) to build and deploy data solutions.

- Collaboration : Collaborate with data scientists, analysts, and other engineers to understand data requirements and deliver effective solutions.

- Documentation : Create and maintain clear and concise documentation for data pipelines and processes.

- Troubleshooting : Identify and resolve data-related issues and performance bottlenecks.

Qualifications :

- Experience : 3-5 years of professional experience as a Data Engineer.

- Strong proficiency in Python and related data engineering libraries (Pandas, NumPy, PySpark).

- Strong SQL skills for data querying and manipulation.

- Proven experience in designing and implementing ETL/ELT processes.

- Experience with data warehousing concepts and technologies.

- Familiarity with cloud data platforms (AWS, Azure, or GCP).

- Understanding of data modeling principles.

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills.

- Proficient with Git.

- Bachelor's degree in Computer Science, Information Technology, or a related field.

Preferred Qualifications :

- Experience with big data technologies (Spark, Hadoop).

- Experience with data orchestration tools (Airflow, Prefect).

- Experience with containerization technologies (Docker, Kubernetes).

- Familiarity with data visualization tools (Tableau, Power BI).

- Experience in building and maintaining data lakes

(ref:hirist.tech)

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