Amdocs India Data Engineer Interview: Rounds, Questions and Preparation

What the job involves

Data Engineers build and maintain the pipelines that move and transform data from source systems into warehouses and analytics platforms. In global tech services companies, they work with SQL, Python, and cloud tools to ensure data is clean, reliable, and available for reporting and machine learning. Day to day involves writing ETL code, debugging data issues, and optimizing queries for performance.

Role and Technical Knowledge

1. 1

   What is the difference between ETL and ELT, and when would you use each?

   Explain that ETL transforms data before loading, while ELT loads raw data first and transforms later. Mention that ELT is common with cloud warehouses due to scalable compute.

2. 2

   How would you design a data pipeline to ingest daily sales data from multiple sources?

   Cover source identification, extraction methods (APIs, files), scheduling (e.g., cron or Airflow), transformation steps, and loading into a warehouse. Mention error handling and data quality checks.

3. 3

   Explain the difference between a data lake and a data warehouse.

   Describe data lake as raw, schema-on-read storage for all data types, and warehouse as structured, schema-on-write for analytics. Give examples like S3 vs Redshift.

4. 4

   What are the key considerations for partitioning and bucketing in Hive or Spark?

   Partitioning divides data by column values to speed queries, bucketing hashes data into fixed files for joins. Mention that over-partitioning can cause small files problem.

Practical Scenarios and Problem Solving

1. 5

   You notice a daily pipeline has been failing for three days. How do you debug and resolve it?

   Start by checking logs and error messages, verify source data availability, and test each step. Then fix the root cause, backfill missing data, and add monitoring alerts.

2. 6

   Write a SQL query to find the second highest salary from an Employee table.

   Use a subquery with MAX and a condition, or use LIMIT with OFFSET after ordering. Mention handling ties and nulls.

3. 7

   How would you handle duplicate records in a dataset before loading into a warehouse?

   Use SQL window functions like ROW_NUMBER to identify duplicates, then deduplicate based on business keys. Explain the importance of defining what a duplicate means.

4. 8

   Your manager asks you to optimize a slow-running query on a large table. What steps do you take?

   Check execution plan, add indexes on filter columns, avoid SELECT *, and consider partitioning. Mention that sometimes rewriting the query or using temporary tables helps.

Behavioural and Situational Questions

1. 9

   Tell me about a time you had to learn a new technology quickly for a project.

   Use STAR method: describe the situation, the technology, how you learned it (courses, docs, practice), and the positive outcome. Show eagerness to learn.

2. 10

   Describe a situation where you made a mistake in your work. How did you handle it?

   Be honest about a small mistake, focus on how you identified it, communicated it, and fixed it. Emphasize learning and preventing recurrence.

3. 11

   How do you prioritize tasks when you have multiple deadlines?

   Mention assessing urgency and impact, communicating with stakeholders, and using tools like to-do lists or Kanban. Give an example from college projects.

4. 12

   Give an example of working in a team where there was a conflict. How did you resolve it?

   Show that you listened to all sides, focused on the goal, and suggested a compromise. Avoid blaming others and highlight the positive result.

HR and Company Fit

1. 13

   Why do you want to work as a Data Engineer in a global tech services company?

   Connect your interest in data and problem solving to the scale and variety of projects. Mention exposure to multiple clients and technologies.

2. 14

   Where do you see yourself in three years?

   Show ambition to grow into a senior data engineer role, deepening expertise in cloud and big data. Align with the company's career path.

3. 15

   Are you willing to relocate or work in different shifts if required?

   Be honest but flexible. Global companies may have clients in different time zones, so express willingness to adapt.

4. 16

   What do you know about our company and why should we hire you?

   Research the company's services, values, and recent news. Highlight your skills match and enthusiasm to contribute from day one.