Company
Name :

Job
Title :

Principal
Data Engineer

Qualification
:

Any
graduation

Experience
:

10+
Years

Must
Have Skills :

- 10+
years of experience in data engineering and enterprise data
platform development.

- Strong
hands -on experience designing and implementing enterprise data
pipelines and data platforms.

- Deep
expertise in SQL, including complex joins, query optimization,
and analytical workloads.

- Hands -on
experience with SSIS, stored procedures, and database -level
transformations.

- Strong
understanding of data lakes, lakehouse architectures, and data
warehouses.

- Experience
working with structured, semi -structured, and unstructured data.

- Strong
experience with Databricks and modern data engineering practices.

- Experience
with Azure data services such as Azure Data Factory, Azure
Synapse, and Azure Data Lake Storage, or equivalent cloud
technologies.

- Experience
implementing data quality, governance, and compliance frameworks
in enterprise environments.

- Ability
to design, build, troubleshoot, and optimize production -grade
data systems independently.

- Strong
collaboration and communication skills across engineering,
analytics, ML, and business teams.

Valuable




to Have Skills :

Experience
with streaming
platforms (Kafka, Spark Streaming, Flink).

- Knowledge
of DevOps
and CI/CD practices for data engineering.

- Familiarity
with containerization
and orchestration (Docker, Kubernetes).

- Exposure
to ML
data pipelines and feature engineering.

- Relevant
certifications in cloud
or data engineering.

Roles
and Responsibilities :

- Architect,
build, and maintain end -to -end batch and streaming data pipelines
for enterprise data platforms.

- Design
and implement scalable data lake and lakehouse architectures to
support analytics, reporting, and ML workloads.

- Develop
and manage data ingestion frameworks from multiple source systems
into centralized data platforms.

- Define
and enforce enterprise data quality frameworks, including
validation rules, reconciliation checks, and monitoring.

- Implement
data governance practices, including metadata management, lineage
tracking, and access controls.

- Design
and optimize data transformation workflows using SQL, stored
procedures, and ETL/ELT patterns.

- Modernize
legacy ETL solutions into cloud -native, scalable data pipelines.

- Architect
and support modern data services including Databricks, Azure Data
Factory, Azure Synapse, and Azure Data Lake Storage.

- Optimize
data models and performance for analytical and downstream
consumption.

- Collaborate
closely with business, analytics, and ML teams to translate data
requirements into scalable data solutions.

- Provide
technical leadership, set engineering standards, and mentor other
data engineers as needed.

- Support
production data platforms with a hands -on operational mindset,
including troubleshooting and performance tuning.

Location
:

Bangalore
and Chennai

CTC
Range :

25
LPA

Notice
period :

Immediate

Shift
Timings :

3pm -12pm/2pm -11pm

Mode
of Interview :

Virtual

Mode
of Work :

5
days work from office

Mode
of Hire :

Permanent

Note
: