Siruseri Chennai Tamil Nadu Data engineering assistant manager Jobs – 2 Open Jobs Today

Data Engineering - Assistant Manager
Guardian Management Services —Thoraipakkam, Chennai, Tamil Nadu
- Full-time
- Azure
- Computer Science
- Databases
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12d
Data Scientist - Assistant Manager
Guardian Management Services —Thoraipakkam, Chennai, Tamil Nadu
- Full-time
- Azure
- Computer Science
- Master's degree
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12d

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Data Engineering - Assistant Manager
Guardian Management Services —Thoraipakkam, Chennai, Tamil Nadu
We are looking for an experienced Data Engineer to design, build, and maintain scalable data pipelines and. Design and maintain data models (conceptual, logical…
Quick apply
12d
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Data Engineering - Assistant Manager

Guardian Management Services -
Thoraipakkam, Chennai, Tamil Nadu

Quick apply

Job details

Permanent | Full-time
12 days ago

Qualifications

BCS
CI/CD
Data modelling
Azure
Computer Science
Cassandra
Relational databases
Big data
Spark
Microsoft SQL Server
NoSQL
Git
MongoDB
Databases
SQL
AWS
Bachelor's degree
Machine learning
PostgreSQL
Distributed systems
Scala
Continuous integration
APIs
ETL
S3
Apache
Kafka
Redshift
DynamoDB
Data warehouse
Python
MySQL
Hadoop

Full job description

We are looking for an experienced Data Engineer to design, build, and maintain scalable data pipelines and

infrastructure that power analytics, reporting, and machine learning initiatives across the organization. The

ideal candidate has a strong foundation in data modelling, distributed systems, and cloud-based data

platforms, with a track record of delivering reliable, high-performance data solutions.

Key Responsibilities

Design, build, and optimize scalable ETL/ELT pipelines to ingest, transform, and load data from

diverse sources (databases, APIs, streaming platforms, third-party systems)

Develop and maintain data warehouse/data lake architectures, ensuring data quality, consistency,

and reliability

Collaborate with data scientists, analysts, and product teams to understand data requirements and

deliver well-structured, accessible datasets

Build and maintain batch and real-time streaming data pipelines using tools like Apache Spark,

Kafka, or Airflow

Implement data quality checks, monitoring, and alerting to ensure pipeline reliability and data

integrity

Optimize database and query performance for large-scale datasets

Design and maintain data models (conceptual, logical, physical) and schemas that support analytics

and application needs

Work with cloud platforms (AWS/Azure/GCP) to manage data infrastructure, storage, and compute

resources

Implement and enforce data governance, security, and compliance best practices

Participate in code reviews, CI/CD pipeline development, and infrastructure-as-code practices

Document data pipelines, architecture, and processes for team knowledge sharing

Troubleshoot and resolve production data pipeline issues in a timely manner

Required Skills & Qualifications

Bachelor's degree in Computer Science, Engineering, or a related field

8+ years of hands-on experience as a Data Engineer or in a similar role

Strong programming skills in Python and/or Scala; solid SQL expertise

Experience with ETL/ELT tools and orchestration frameworks (Apache Airflow, dbt, Luigi, or

similar)

Hands-on experience with big data technologies (Apache Spark, Hadoop, Kafka)

Proficiency with relational databases (PostgreSQL, MySQL, SQL Server) and NoSQL databases

(MongoDB, Cassandra, DynamoDB)

Experience working with cloud data platforms and services (AWS Redshift/Glue/S3, Azure Data

Factory/Synapse, GCP BigQuery/Dataflow)

Solid understanding of data modeling concepts — entity relationships, cardinality, normalization,

and dimensional modeling (star/snowflake schemas)

Experience with data warehousing solutions (Snowflake, Redshift, BigQuery, Databricks)

Familiarity with version control (Git) and CI/CD practices

Understanding of data governance, security, and privacy best practices (GDPR, data masking, access

controls)

Strong problem-solving skills and ability to work with large, complex datasets

Work Location: In person

Quick apply

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