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Prana Tree
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Data Engineer

Data Engineer

Prana Tree

8 years

0 Lacs

chennai tamil nadu india

Posted:3 days ago| Platform:

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Skills Required

data design support analytics ai strategy architecture governance security integration engineering leadership efficiency agile strategies consistency usability processing query indexing storage scalability interoperability drive compliance controls tracking monitoring planning technology cutting databricks nosql etl code collaboration sql olap apache spark software git jenkins maven testing devops ml pipeline service

Work Mode

On-site

Job Type

Contractual

Job Description

Job Title: Data Engineer

Location:

Work Mode:

Experience:

Role Description

Data Engineer

data strategy, architecture, governance, security, and operational efficiency

modern cloud-based data architectures

Roles & Responsibilities

Design and implement scalable, modular, and future-proof data architectures for enterprise initiatives.
Develop enterprise-wide data frameworks that enable governed, secure, and accessible data across various business domains.
Define data modeling strategies to support structured and unstructured data, ensuring efficiency, consistency, and usability across analytical platforms.
Develop high-performance data pipelines for batch and real-time data processing by integrating APIs, streaming sources, transactional systems, and external data platforms.
Optimize query performance, indexing, caching, and storage strategies to enhance scalability, cost efficiency, and analytical capabilities.
Establish data interoperability frameworks that enable seamless integration across multiple data sources and platforms.
Drive data governance strategies, ensuring security, compliance, access controls, and lineage tracking are embedded into enterprise data solutions.
Implement
DataOps best practices
, including CI/CD for data pipelines, automated monitoring, and proactive issue resolution to improve operational efficiency.
Lead
Scaled Agile (SAFe)
practices, including Program Increment (PI) Planning, Sprint Planning, and Agile ceremonies, ensuring iterative delivery of enterprise data capabilities.
Collaborate with business stakeholders, product teams, and technology leaders to align data architecture strategies with organizational goals.
Leverage emerging data technologies and trends to ensure adoption of cutting-edge, scalable, and competitive data solutions

Must-Have Skills

Proven experience in
data architecture, enterprise data management,
and
cloud-based analytics solutions.
Expertise in
Databricks, cloud-native data platforms,
and
distributed computing frameworks.
Strong proficiency in
data modeling techniques
— dimensional modeling, NoSQL, and data virtualization.
Hands-on experience designing
high-performance ETL/ELT pipelines
and
real-time data processing
solutions.
Deep understanding of
data governance, security, metadata management,
and
access control frameworks.
Experience with
CI/CD for data solutions, DataOps automation,
and
infrastructure as code (IaC).
Proven collaboration with cross-functional teams, including business executives, data engineers, and analytics teams.
Strong
problem-solving, strategic thinking,
and
technical leadership
skills.
Experience with
SQL/NoSQL databases,
including
vector databases for large language models.
Experience in
data modeling and performance tuning
for both OLAP and OLTP databases.
Proficiency with
Apache Spark, Apache Airflow.
Familiarity with
software engineering best practices
— version control (Git, Subversion), CI/CD (Jenkins, Maven), automated testing, and DevOps workflows.

Good-to-Have Skills

Experience with
Data Mesh architectures
and
federated data governance models.
Cloud or enterprise architecture certifications.
Knowledge of
AI/ML pipeline integration
within enterprise data architectures.
Familiarity with
BI and analytics platforms
for enabling self-service analytics and enterprise reporting.

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