Job Description

Job Title: Data Engineer

Experience:

5 Years

Location:

Bangalore, India

About the Role

We are seeking a highly experienced

Data Engineer

with strong expertise in

Apache Airflow

and

Python

to lead complex data workflow migrations and build scalable data architecture. You will design, optimize, and maintain data pipelines that power our business analytics and data-driven decision-making. This role demands deep knowledge of both NoSQL (MongoDB) and relational databases, and experience in streamlining CI/CD processes for data workloads.

Key Responsibilities

Lead the migration of Jenkins-based data pipelines to

Apache Airflow

, improving orchestration, scheduling, and reliability. Design and implement robust, scalable data workflows using

Airflow

and

Python

, ensuring reliability, modularity, and fault tolerance. Architect and optimize data storage solutions using

MongoDB

(NoSQL) as well as

MySQL / PostgreSQL

(relational), balancing performance and cost. Collaborate with cross-functional teams (data scientists, analysts, engineers) to build integrated data pipelines and delivery mechanisms. Implement data validation and quality checks to ensure accuracy, consistency, and reliability across all processes. Airbyte+2Airbyte+2 Monitor, profile, and tune data workflows for performance, throughput, and resource utilization. Build and maintain CI/CD practices specifically tailored for data pipelines, enabling rapid delivery and stable deployments. Document data workflows, architecture patterns, and processes to support maintainability and knowledge sharing. Stay current on data engineering best practices, emerging tools, and orchestration frameworks.

Required Skills & Expertise

Strong experience in

Apache Airflow

and writing DAGs in Python. Proficiency in

Python

for building data ingestion and transformation logic. Experience migrating or managing

CI/CD pipelines

(e.g., Jenkins ? Airflow). Deep understanding of

MongoDB

(NoSQL) as well as

MySQL / PostgreSQL

or other relational databases. Expertise in designing, building, and maintaining

data pipelines

and workflow orchestration systems. Solid experience in ensuring data quality, reliability, and performance in production pipelines. Strong problem-solving, debugging, and analytical skills. Excellent communication and collaboration skills, with ability to work across cross-functional teams.

Nice-to-Have

Experience with

Docker

,

AWS

, or

GCP

. Familiarity with

Spark

for large-scale data processing. X0PA AI Experience using

Git

and REST APIs in data engineering context. Understanding of data governance, data lineage, and metadata management. Taggd

Soft Skills

Strong

analytical thinking

and problem-solving mindset. Excellent

ownership

-- ability to lead and drive data architecture initiatives. Good

communication

skills to articulate complex data ideas to technical and non-technical stakeholders. Team player, able to collaborate effectively with engineers, data scientists, and product teams.
If you like, I can also:
? Create a

LinkedIn?ready job posting

? Provide a

short, catchy version for job boards

? Craft a

technical deep-dive JD

specifically for senior data engineering roles

Do you want me to do one?

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Job Type: Full-time

Pay: ?1,000,000.00 - ?1,500,000.00 per year

Work Location: In person