Sr Test Engineer - Automation

Job Description

Current JD - Data Quality Engineer (Role). Ready to work as DQE. Location - Pune/Chennai 1. Experience in Python /Java programming required to automate data analysis tasks - Must have 2. Experience in writing Advance SQL queries (Topics listed below) - Must have 3. Knowledge of BDD and Cucumber - Good to have 4. Knowledge of Agile methodologies, CI/CD etc. - Good to have 5. Hands on Functional Data / ETL Testing Experience - Good to have Advanced SQL topics delve into more complex database operations and query optimization techniques. Here are some key areas to explore: Window Functions . RANK, DENSE_RANK, ROW_NUMBER: Assign a rank to each row within a partition. . LEAD, LAG: Access rows preceding or following the current row within a partition. . PARTITION BY, ORDER BY: Define partitions and the order within each partition. . Window frames: Specify the range of rows included in a window function calculation. Common Table Expressions (CTEs) . Recursive CTEs: Create recursive queries to process hierarchical data. . Multiple CTEs: Use multiple CTEs to break down complex queries into smaller, more manageable parts. Subqueries . Correlated subqueries: Subqueries that reference columns from the outer query. . Scalar subqueries: Subqueries that return a single value. . EXISTS and NOT EXISTS: Test for the existence or non-existence of rows in a subquery. Analytical Functions . CUME_DIST: Calculate the cumulative distribution of a value within a group. . PERCENT_RANK: Calculate the percentile rank of a value within a group. . NTILE: Divide a result set into a specified number of groups. Full-Text Search . Full-text indexes: Create indexes that support full-text search capabilities. . Ranking functions: Rank search results based on relevance. . Stop words: Exclude common words from search queries. Hierarchical Queries . CONNECT BY PRIOR: Traverse hierarchical relationships in a table. . START WITH: Specify the starting point for a hierarchical query. Optimization Techniques . Indexes: Create appropriate indexes to improve query performance. . Query tuning: Analyze query execution plans and optimize queries. . Materialized views: Pre-calculate and store query results for faster access.