Data Engineer
Cisco Hyderabad, Telangana, India
Job Description
"Unlock the secrets of data engineering at Cisco and propel your career forward in a fast-paced, complex environment."
In this role, you will be responsible for providing accurate and timely foundation data to various functions across Cisco, working closely with cross-functional stakeholders, vendors, technical IT teams, senior leadership, and customers/partners.
As a Data Engineer at Cisco, you will have the opportunity to leverage your analytical skills, advanced data analysis expertise, and technical knowledge to drive innovation and thought leadership within the team.
Why you should learn this:
The demand for skilled Data Engineers is high, with a projected growth rate of 14% by 2028, outpacing the national average.
Expected Salary: $118,000 - $170,000 per year, with experienced Data Engineers earning up to $200,000 or more.
How it works:
- Design, build, and maintain large-scale data systems and pipelines to support business requirements.
- Collaborate with cross-functional teams to identify data requirements, develop data models, and implement data solutions.
- Develop and maintain high-quality data pipelines, data warehouses, and data lakes using various technologies, including Hadoop, Spark, and cloud-based platforms.
- Conduct exploratory data analysis (EDA) to uncover trends, identify anomalies, and provide data-driven insights to inform business decisions.
Core Concepts to Master
Data Ingestion and Processing
Learn about various data ingestion tools, such as Apache NiFi, Apache Beam, and AWS Glue, and how to process large datasets using Apache Spark, Hadoop, and cloud-based platforms.
Data Warehousing and Lakehouse
Discover the concepts of data warehousing and lakehouse, including data modeling, ETL, and data governance, and learn how to design and implement scalable data warehouses and lakehouses using technologies like Snowflake, Redshift, and Databricks.
Data Engineering Tools and Technologies
Explore the world of data engineering tools and technologies, including data pipelining, data governance, and data quality, and learn how to use tools like Apache Airflow, Apache Flink, and AWS Glue to automate data workflows and ensure data quality.
Cloud-Based Data Platforms
Learn about the latest cloud-based data platforms, including AWS Lake Formation, Google Cloud Data Fusion, and Azure Synapse Analytics, and discover how to design and implement scalable data platforms using cloud-based technologies.
Interview Questions (Beginner)
- What is data engineering, and how does it differ from data science?
- Can you describe a time when you had to troubleshoot a complex data issue?
- How do you approach data modeling, and what tools do you use to design data models?
Job Overview
Advance Questions
- • Can you explain the concept of data governance, and how do you implement data governance in a large-scale data system?
- • How do you design and implement a scalable data pipeline using Apache Beam or Apache NiFi?
- • Can you describe a time when you had to optimize a data workflow to improve performance, and what strategies did you use to achieve this?