About The Company The tech space is crowded, but most solutions feel like they’re cut from the same cloth — missing the mark on what businesses truly need. Organizations are chasing innovation, but too often, it comes at the expense of flexibility, independence, and real technological depth. At Dawn Technologies is a niche company laser-focused on delivering specialized tech solutions in Gen AI, Data Engineering, and Backend Systems. What sets us apart is our commitment to the technologists — the creators, problem-solvers, and innovators who bring true value to transformation.

We believe that teamwork plus talent equals exceptional results. We are looking for teammates who are great problem solvers and enjoy collaborating within a team to achieve big outcomes.

–Data Engineer

Job Title: Data Engineer

Job Family: Engineering / Data & Analytics

Experience: 4+ years

Location: Bangalore

Role Overview

Looking for a hands-on Data Engineer to design, develop and maintain scalable data pipelines, data-processing services and integration solutions supporting enterprise applications, analytics and AI-enabled solutions.

The candidate should possess strong Python and SQL programming skills, along with practical experience in data ingestion, ETL/ELT, API integration, relational and NoSQL databases, data modeling and data-quality engineering.

The role requires someone who can independently develop production-quality data components while collaborating with application developers, architects, AI/ML engineers, business analysts and other engineering teams.

Key Responsibilities

- Design, develop and maintain scalable data ingestion, transformation and processing pipelines.
- Develop production-quality data engineering components using Python.
- Write complex and optimized SQL queries for data extraction, transformation, validation and analysis.
- Develop and maintain ETL/ELT pipelines for structured and semi-structured data.
- Integrate data from databases, enterprise applications, REST APIs,



files and other data sources.
- Develop reusable Python modules for ingestion, transformation, validation, logging and exception handling.
- Design and implement relational database schemas and data models.
- Work with SQL and NoSQL databases based on application requirements.
- Implement data-quality controls including validation, reconciliation, deduplication and completeness checks.
- Develop and consume REST APIs for data integration.
- Work with enterprise search technologies such as Elasticsearch/OpenSearch or Apache Solr where required.
- Optimize database queries and pipelines for performance and scalability.
- Implement appropriate error handling, retry, logging and monitoring mechanisms.
- Develop automated unit, integration and data-quality tests.
- Troubleshoot data, database, API and pipeline-related issues across development and production environments.
- Follow Git-based development, code-review and CI/CD practices.
- Work collaboratively with architects and engineering teams to translate requirements into technical implementations.
- Create and maintain appropriate technical documentation.

Required Technical Skills

Skill Area

Expected Proficiency

Python

Solid – Mandatory

SQL

Strong/Advanced – Mandatory

Data Engineering

ETL/ELT, ingestion, transformation, validation

Python Libraries

Pandas, NumPy, PyArrow or equivalent

Relational Databases

SQL Server / PostgreSQL / MySQL

NoSQL

MongoDB / document databases or equivalent

API Integration

REST APIs, JSON, authentication

Data Modeling

Relational modeling, schema design, dimensional concepts

Data Formats





JSON, CSV, XML, Parquet

Search Technologies

Elasticsearch/OpenSearch, Apache Solr

Version Control

Git / GitHub / GitLab

Testing

PyTest, unit testing, integration and data-quality testing

Linux

Shell commands, scripting and troubleshooting

Containerization

Docker

CI/CD

Basic understanding of automated build/test/deployment pipelines

SQL Skills The candidate should have practical experience with:

Complex Joins • CTEs • Subqueries • Window Functions • Aggregations • Views • Stored Procedures • Transactions • Indexes • Query Execution Plans • Query Optimization The engineer should understand how database design and indexing decisions affect application and pipeline performance.

Data Engineering Skills The candidate should understand an end-to-end data flow such as:

Source Systems → Ingestion → Validation → Transformation → Data Quality → Storage → Search/Analytics/Application Consumption

Experience should include

- Batch data processing
- Incremental data loading
- ETL/ELT
- Schema validation
- Data cleansing
- Deduplication
- Reconciliation
- Error handling
- Retry/recovery
- Data lineage fundamentals
- Metadata handling

AI/GenAI exposure – desirable

Educational Qualification

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science or a related technical discipline, or equivalent practical experience.

Professional Competencies The candidate should demonstrate:

- Strong analytical and problem-solving skills
- Good programming discipline
- Ability to independently troubleshoot technical issues
- Understanding of software engineering best practices
- Ability to work within Agile development teams
- Effective communication and collaboration
- Ability to understand technical requirements and translate them into working solutions
- Willingness to learn emerging data and AI technologies

📌 Data Engineer (Bengaluru)
🏢 At Dawn Technologies
📍 Bengaluru