Maharani Bagh Delhi Delhi Management trainee Jobs – 128 Open Jobs Today

AI Engineer
DS Group —Noida, Uttar Pradesh
- Full-time
- Computer Science
- B.Sc
- Master's degree
Trainee Equity Trader – Training Provided | Path to Associate Trader
AArnisha investments —Delhi, Delhi
- ₹8,715.94 - ₹49,791.93 a month
- Hybrid work
- Microsoft Excel
- Finance
- Analysis skills
Quick apply
6h
Meta Ads Executive
GTF Technologies —Noida, Uttar Pradesh
- ₹10,029.11 - ₹32,537.45 a month
- Full-time
- Marketing
- Analysis skills
- Bachelor's degree
Quick apply
Management Trainees
Bharatiya Global Infomedia —Noida, Uttar Pradesh
- Master's degree
- Business Administration
- MBA
HR Executive
Sofcon India Pvt. Ltd. —Pitampura, Delhi, Delhi
- ₹20,000 - ₹22,000 a month
- Full-time
- Microsoft Excel
- English
- Bachelor's degree
- Paid time off
- Paid sick time
Quick apply
6h
Accounts & Administration Trainee
Pinnacles —Noida, Uttar Pradesh
- ₹15,094.33 - ₹20,663.75 a month
- Part-time
- Microsoft Excel
- Inventory control
- Inventory management
- Paid time off
- Cell phone reimbursement
Quick apply
Management Trainee ( Online Bidding)
Web Arena Technologies —South East District, Delhi
- Computer Science
- Sales
- Bachelor's degree
Solar Engineer
kasth Enterprise —Rohini, Delhi, Delhi
- ₹35,000.00 - ₹45,554.63 a month
- Full-time
- Programmable logic controllers
- Electrical experience
- Bachelor's degree
- Health insurance
Quick apply
HR Trainee
TNS Networking Solutions Pvt.Ltd. —Chhattarpur, Delhi, Delhi
- ₹10,000 - ₹15,000 a month
- Full-time
- Microsoft Office
- Bachelor's degree
- Human resources
- Health insurance
Quick apply
1d
Trainee Clinical Research
WorkSure —Delhi, Delhi
- Full-time
- Master's degree
- Organisational skills
- Communication skills
Trainee Company Secretary
Prabhatam Group —Central District, Delhi
- ₹10,000 - ₹20,000 a month
- Full-time
- English
- Microsoft Office
- Accounting
Quick apply
Business Development Trainee
PRINCE AND UMESH CONSTRUCTIONS PRIVATE LIMITED —Ghaziabad, Uttar Pradesh
- ₹20,000 - ₹30,000 a month
- Full-time
- Sales
- English
- Microsoft Office
Quick apply
Management Trainee - Sales & Marketing
AD2Click Media —Noida Sector 62, Noida, Uttar Pradesh
- ₹8,000 - ₹10,000 a month
- In-person
- Internship
- Communication skills
Quick apply
Sales Intern
Pioneer E Solutions —Bhikaji Cama Place, Delhi
- ₹10,000 - ₹12,000 a month
- Master's degree
- Business development
- Bachelor's degree
Quick apply
10d
Content Writer - Reddit
Online reputation management —Saket, Delhi
- ₹22,500 - ₹25,000 a month
- Full-time
- Social media management
- In-person
Quick apply
7d
Executive - Business Development
Flexsin —Noida, Uttar Pradesh
- CRM software
- English
- Business development
Business Development Management Trainee
Azeus Group of Companies —Noida, Uttar Pradesh
- Call employer
- Bachelor's degree
- Travel
- Communication skills
Meta Ads Trainee
GTF Technologies —Noida, Uttar Pradesh
- ₹15,000 - ₹20,000 a month
- Full-time
- Marketing
- Analysis skills
- Bachelor's degree
Quick apply
IT Sales Trainee
Wildnet Technologies —Noida, Uttar Pradesh
- Full-time
- Microsoft Powerpoint
- Microsoft Word
- Microsoft Excel
Quick apply
Management Trainee - Business Development
Corpseed —Noida, Uttar Pradesh
- Bachelor's degree

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AI Engineer

DS Group -
Noida, Uttar Pradesh

Apply Now

Job details

Full-time

Qualifications

Computer Science
React
Relational databases
B.Sc
NumPy
Configuration management
Master's degree
Databases
SQL
MCA
Pandas
Science
Bachelor's degree
Machine learning
REST
APIs
B.E.
Data science
AI
Communication skills
Python
Debugging

Full job description

Designation: SENIOR EXECUTIVE
Location: India UTTAR PRADESH Noida
Group: DS Group
Entity: Dharampal Satyapal Strategic Consultants LLP
SBU: DHARAMPAL SATYAPAL STRATEGIC CONSULTANTS LLP
Department: INFORMATION TECHNOLOGY
Function: DATA ANALYTICS

Job Description:

Job Title: Graduate Trainee / Junior Data & Analytics Engineer

Employment Level: Fresher / Entry Level

ROLE PURPOSE

We are looking for a curious, technically strong fresher who wants to build a career across data engineering, analytics, database management, and dashboard development. The role is suitable for recent graduates with excellent SQL fundamentals, strong Python programming ability, and a clear understanding of how data moves from operational systems into reporting and analytical solutions.

The selected candidate will work with experienced team members to build reliable data pipelines, validate and transform data, create dashboards, automate recurring activities, and help business teams make better decisions. Prior full-time work experience is not required; however, candidates must be able to demonstrate their knowledge through academic projects, internships, personal projects, certifications, or a practical technical assessment.

KEY RESPONSIBILITIES

Understand business requirements and convert them into clear data fields, source-to-target mappings, transformation rules, validation checks, and expected outputs.

Write accurate and efficient SQL queries for data extraction, joining, aggregation, reconciliation, analysis, and reporting.

Assist in building and maintaining data pipelines that move data between operational databases, files, APIs, data warehouses, and analytical platforms.

Use Python to extract, clean, transform, validate, and load structured data.

Develop reusable Python scripts and small applications for automation, reporting, data-quality checks, and recurring analytical tasks.

Build clear and user-friendly dashboards using Python-based visualization or dashboard frameworks and, where required, standard business-intelligence tools.

Analyse data to identify trends, exceptions, missing values, duplicates, inconsistent master data, and unusual business movements.

Reconcile dashboard and report outputs with source data before release.

Support incremental loads, scheduled jobs, error handling, logging, monitoring, and recovery of failed data-processing tasks.

Document database objects, pipeline logic, field definitions, business rules, assumptions, dependencies, and refresh schedules.

Work with business users, analysts, and technology teams to troubleshoot data issues and improve the reliability of reporting.

Follow secure coding, data-access, version-control, testing, and documentation practices.

Continuously learn new data technologies and contribute ideas for improving automation, performance, and user experience.

MANDATORY TECHNICAL KNOWLEDGE

1. SQL and database fundamentals

Very strong command of SQL, including joins, subqueries, common table expressions, window functions, grouping, conditional aggregation, set operations, date functions, and data-cleaning logic.

Ability to solve SQL problems involving duplicates, nulls, changing records, mismatched data types, multiple levels of granularity, and incomplete source data.

Sound knowledge of relational database concepts, tables, keys, constraints, relationships, normalization, denormalization, views, indexes, and transactions.

Basic understanding of query execution plans and the factors that affect database and query performance.

Ability to design a simple database schema and explain why particular tables, keys, relationships, and indexes were selected.

Strong interest in database management, data accuracy, data lineage, and source-of-truth controls.

2. Python programming

Strong programming fundamentals in Python, including functions, classes, modules, collections, file handling, exception handling, and reusable code design.

Hands-on knowledge of data-processing libraries such as pandas and NumPy.

Ability to connect Python applications to databases, execute parameterized queries, process files, and consume REST APIs.

Understanding of logging, debugging, configuration management, virtual environments, testing, and basic performance considerations.

Ability to write readable, modular, and documented code instead of one-time scripts.

Exposure to Python-based dashboards or visualisation tools such as Streamlit, Plotly, Dash, Matplotlib, Seaborn, or similar frameworks.

3. Data-pipeline understanding

Clear understanding of ETL/ELT concepts and the stages involved in extracting, validating, transforming, and loading data.

Knowledge of batch processing, incremental loading, scheduling, dependencies, error handling, retries, audit fields, and reconciliation.

Ability to explain how a data pipeline should prevent duplicate loads, identify failed records, and prove that the target data matches the source.

Familiarity with data warehouses, analytical databases, data lakes, or modern data platforms is useful.

Awareness of orchestration, monitoring, and data-quality concepts will be an advantage.

4. Dashboard and analytical thinking

Ability to choose appropriate charts, filters, KPIs, drill-downs, and layouts for a business question.

Strong numerical and logical reasoning with the ability to understand what a metric means and why it may have changed.

Ability to build simple interactive dashboards using Python and explain the data and calculation logic behind them.

Exposure to any established business-intelligence or reporting tool is useful, but strong Python, SQL, and data understanding are the priority.

Good attention to usability, performance, accuracy, and clarity when presenting data.

QUALIFICATIONS

B.E./B.Tech, BCA, MCA, B.Sc./M.Sc., or equivalent qualification in Computer Science, Information Technology, Data Science, Statistics, Mathematics, Engineering, or a related discipline.

Fresh graduates and candidates with internship experience may apply.

Academic projects, personal projects, coding profiles, dashboards, database designs, or data-pipeline demonstrations will be considered as valuable evidence of capability.

Relevant certifications are welcome but will not replace practical knowledge.

WHAT WE VALUE

Strong problem-solving ability and willingness to investigate data instead of accepting results without validation.

Curiosity about business processes and the ability to ask clear questions.

Ownership, discipline, attention to detail, and a learning mindset.

Clear written and verbal communication.

Ability to explain technical work in simple language and collaborate respectfully with both technical and non-technical colleagues.

SELECTION APPROACH

The selection process may include a practical assessment covering advanced SQL, database design, Python programming, data transformation, pipeline logic, data validation, and dashboard creation. Candidates may also be asked to explain one academic, internship, or personal project in detail, including the problem, data model, code, testing approach, and final outcome.

Skills:

SQL DBA -L2

Python

Machine Learning

React

Apply Now

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