Principal Data Engineer

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.
  

Good
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
: