SQL & Database Engineering Tutor / Trainer

Location: Hyderabad, Telangana On-site

Experience: 810 Years

Engagement: Long-term teaching engagement 23 years

Schedule: Monday–Saturday, 9:00 AM–2:00 PM

Batch Size: 80–100 students

Batch Duration: 3 months

About the Program

We are running a practical Data Engineering Skill Development Program designed to provide graduates with industry-relevant skills in Python, SQL, Data Engineering and Generative AI. Each batch runs for three months and typically consists of

80–100 students. The program combines classroom learning with hands-on practice, assignments, assessments, mentoring and an integrated capstone project. We are looking for an experienced SQL & Database Engineering Tutor who can take ownership of the SQL curriculum and build strong SQL and database fundamentals that directly support students’ Data

Engineering journey.

Key Responsibilities

- Conduct classroom sessions Monday–Saturday, 9:00 AM–2:00 PM at our training institute in Hyderabad.
- Teach SQL from fundamentals through advanced, Data Engineering-oriented SQL.
- Conduct hands-on SQL practice using realistic business datasets.
- Explain database concepts using real-world application and Data Engineering examples.
- Design, assign and evaluate practical exercises and assignments.
- Conduct doubt-clearing and problem-solving sessions.
- Mentor students during SQL projects and the integrated Data Engineering project.
- Evaluate students through assignments, quizzes, practical assessments and projects.
- Coordinate with Python and Data Engineering tutors to ensure smooth curriculum handoffs.
- Help students understand both how to write SQL and why a particular approach is appropriate for a Data Engineering problem.
- Use realistic datasets such as customers, loans, transactions and payments.
- Continuously improve teaching material and practical exercises.

Curriculum

1. Database Fundamentals

- Database, DBMS and RDBMS
- Tables,



rows and columns
- Primary/foreign keys and relationships
- NULL and data types
- Constraints
- Application ® Service ® Database architecture
- Operational vs analytical databases
- OLTP vs OLAP

1. SQL Fundamentals

- SELECT, DISTINCT, WHERE, ORDER BY
- Filtering and logical operators
- IN, BETWEEN, LIKE
- NULL handling
- Aliases and expressions

1. DDL, DML, DQL, TCL & DCL

- CREATE, ALTER, DROP, TRUNCATE
- INSERT, UPDATE, DELETE, SELECT
- COMMIT, ROLLBACK, SAVEPOINT
- GRANT and REVOKE

1. Constraints

- Primary Key
- Foreign Key
- UNIQUE
- NOT NULL
- CHECK
- DEFAULT
- Referential integrity

1. SQL Functions

- String, numeric and date functions
- Conversion functions
- CASE
- COALESCE and NULLIF
- Data cleansing with SQL

1. Aggregations

- COUNT, SUM, AVG, MIN, MAX
- GROUP BY and HAVING
- Business-oriented aggregation

1. Joins

- INNER, LEFT, RIGHT and FULL JOIN
- CROSS and SELF JOIN
- Join cardinality
- One-to-many/many-to-many
- Duplicate explosion and NULL behaviour
- Join troubleshooting

1. Advanced SQL

- Scalar, multi-row and correlated subqueries
- EXISTS / NOT EXISTS
- UNION / UNION ALL / INTERSECT / EXCEPT
- CTEs and multiple CTEs
- Recursive CTE introduction

1. Analytical SQL

- OVER, PARTITION BY and ORDER BY
- ROW_NUMBER, RANK, DENSE_RANK, NTILE
- LAG and LEAD
- Running totals and moving averages
- Top-N and month-over-month analysis

1. SQL for Data Engineering

- Raw, staging, transformation and target tables
- Full vs incremental loads
- Upsert / MERGE
- Watermarks / high-water marks
- Idempotency
- Deduplication




- Source-to-target transformations

1. Data Modeling

- ER modeling
- Normalization and denormalization
- Facts and dimensions
- Grain and measures
- Star and snowflake schemas
- Natural vs surrogate keys

1. Slowly Changing Dimensions

- SCD Type 1
- SCD Type 2
- Effective/end dates
- Current flags
- Historical data management
- SQL implementation

1. SQL Performance

- Indexes and composite indexes
- Selectivity
- EXPLAIN / execution plans
- Query, join and filter optimization
- Partitioning concepts

1. Data Quality & Production SQL

- Duplicate and NULL checks
- Referential integrity
- Source-to-target reconciliation
- Views and materialized views
- Transactions and ACID
- Basic security
- Brief exposure to procedures, functions and triggers

Candidate Profile — Must Have

- 8–10 years of professional experience working extensively with SQL and relational databases.
- Strong hands-on experience with complex SQL and analytical SQL.
- Solid understanding of database concepts and data modeling.
- Experience with joins, CTEs, window functions and large datasets.
- Good understanding of ETL/ELT and Data Engineering concepts.
- Experience with data warehousing and dimensional modeling.
- Strong communication and classroom presentation skills.
- Ability to explain complex technical concepts simply.
- Passion for mentoring and developing students.
- Willingness to commit to a 2–3 year teaching engagement.
- Ability to teach Monday–Saturday, 9:00 AM–2:00 PM, on-site in Hyderabad.

Preferred

- Experience as a Data Engineer, Analytics Engineer, Data Analyst, BI Engineer or Database Engineer.
- Experience with MySQL, PostgreSQL, Oracle, SQL Server, Redshift, Snowflake or similar platforms.
- Experience with cloud data platforms and Data Engineering projects.
- Prior corporate training or classroom teaching experience.
- Experience designing SQL assignments and assessments.

📌 SQL Trainer / SQL Tutor with 8 To 10 years of industry experience (Hyderabad)
🏢 Sai Easwaramma Prerana Trust
📍 Hyderabad