Senior Data Engineer
Bengaluru, Karnataka, India
- Experience
- 6–7 years
- Employment
- Full-time
- Work mode
- Onsite
- Salary
- ₹12 L–16 L / year
- Deadline
- Apply by 1 Nov 2026
- Posted
- 2025-04-30
Required skills
| Skill | Experience | Level |
|---|---|---|
| Java (All Versions) | 2+ years | Intermediate |
| Python | 3+ years | Intermediate |
| SQL | 3+ years | Intermediate |
| NoSQL | 3+ years | Intermediate |
| Azure | 4+ years | Intermediate |
| Data Modeling | Not specified | Not specified |
| ETL(Extract, Transform, Load) | Not specified | Not specified |
| Data pipelines | Not specified | Not specified |
| Azure DataBricks | Not specified | Not specified |
| Azure Synapse analytics | Not specified | Not specified |
| Apache Scala | Not specified | Not specified |
| Data Warehousing | Not specified | Not specified |
| Big Data | Not specified | Not specified |
| Tableau | Not specified | Not specified |
| Power BI | Not specified | Not specified |
| CI/CD | Not specified | Not specified |
| Docker | Not specified | Not specified |
About the role
Position Overview
As a Data Engineer, you will play a crucial role in designing, building, and maintaining our data
architecture. You will be responsible for ensuring the availability, integrity, and efficiency of
our data pipelines, enabling our organization to make informed, data-driven decisions.
Responsibilities
Data pipeline development: Design, build, and maintain scalable data pipelines for
ingesting, processing, and transforming data from various sources, ensuring data
quality, scalability, and reliability.
Data modelling: Develop and maintain data models, architecture patterns, schemas,
and structures that support the needs of data analysts, data scientists, and other
stakeholders.
ETL (Extract, Transform, Load): Create and optimize ETL processes to extract data from
diverse sources, transform it into usable formats, and load it into data warehouses or
other storage solutions.
Data governance, quality and validation: Establish and enforce data governance
policies, standards, procedures, and best practices and implement data quality checks,
validation processes, and error handling to ensure the accuracy and consistency of
data.
Performance tuning: Continuously monitor and optimize the performance of data
pipelines to meet business requirements and scalability needs.
Data security: Implement and maintain data security measures to protect sensitive
information and ensure compliance with data privacy regulations.
Collaboration: Work closely with data analysts, data scientists, and other stakeholders
to understand their data requirements and provide support in data access and
availability.
Documentation: Maintain thorough documentation of data engineering processes,
data models, and data dictionaries.
Stay informed: Keep up to date with emerging trends and technologies in data
engineering to ensure our data infrastructure remains cutting-edge.
Qualifications
Bachelor’s degree in computer science, information technology, or a related field
Demonstrable experience of minimum 7 years position as a Senior Data Engineer or
similar, with hands on experience in designing and implementing data lakes, data
warehouses, data modelling, ETL processes, and data transformation pipelines
Experience in Azure cloud-based data platforms (e.g., Azure Synapse Analytics, Fabric,
Databricks etc.).
Microsoft Fabric and Lakehouse experience is an added advantage for this role.
Experience in real time data ingestion and streaming
Proficiency in programming languages such as Python, Java, or Scala
Strong knowledge of database systems (SQL and NoSQL), data warehousing, and big
data technologies
Knowledge of data governance principles, data quality management, and regulatory
compliance
Experience with orchestration services (i.e., Azure Data Factory (ADF), Azure Logic Apps,
Azure Functions, Databricks Jobs, Airflow etc.)
Excellent communications, leadership, and collaboration skills
Ability to work in a fast-paced, dynamic environment and lead multiple projects and
teams to deliver high-quality results
Technical Expertise:
o Programming languages: Python, Java, Scala, and R.
o Data management & databases: Oracle, SAP, SQL, NoSQL, Data Warehousing
o Big data technologies: Apache Hadoop, Spark, Kafka, etc.
o Cloud platforms: Experience with Microsoft Fabric, Azure (Synapse Analytics,
Databricks, Machine Learning, AI Search, Functions, etc.), Databricks on Azure,
o Data governance: Experience with Data governance tools Ab Initio, Informatica,
Collibra, Purview etc.
o Data visualization: Familiarity with Tableau, Power BI
o DevOps & MLOps: CI/CD principles, Docker, MLFlow, Kubernetes
Benefits
Competitive salary and benefits package.
Opportunity to work on cutting-edge technology projects.
Collaborative and innovative work environment.
Professional growth and training opportunities