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Assistant Manager - Data Engineer

Chennai, India

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design, build and optimize ETL/ELT pipelines from databases, APIs and streaming sources

  • Develop and maintain data warehouse and data lake architectures

  • Build batch and real-time streaming pipelines using Spark, Kafka or Airflow

  • Implement data quality checks, monitoring and alerting

  • Design and maintain data models and schemas for analytics and applications

From the employer’s posting
Design, build, and optimize scalable ETL/ELT pipelines to ingest, transform, and load data from diverse sources
Develop and maintain data warehouse/data lake architectures, ensuring data quality, consistency, and reliability
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
Design and maintain data models (conceptual, logical, physical) and schemas that support analytics and application needs
Education & alternatives
Required Skills & Qualifications ● Bachelor's degree in Computer Science, Engineering, or a related field ● 4–6 years of hands-on experience as a Data Engineer or in a similar role

Tools in this posting

  • Python
  • Scala
  • SQL
  • AWS
  • Azure
  • BigQuery
  • Databricks
  • dbt
  • DynamoDB
  • GCP
  • Hadoop
  • Kafka
  • MongoDB
  • MySQL
  • NoSQL
  • PostgreSQL
  • Redshift
  • S3
  • Snowflake
  • Spark
  • SQL Server
  • Airflow
  • Luigi
Source — Tool mentions in context
● 4–6 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)
● 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
● 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)
● 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
● 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)
● 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)
● 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

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Live
First seen by us
Aug 12, 2026 · 78 days ago
Recorded sightings
37
Last seen by us
Oct 29, 2026

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Job description

View original posting ↗

​Assistant Manager -  Data Engineer

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 modeling, 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

●       4–6 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

●        

 

 



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