Senior Data Engineer – ETL & Pipeline Development (7 to 12 yrs)

Senior Data Engineer – ETL & Pipeline Development

Experience : 7 to 12 Years

Location :

Remote (Work from Home) / Bangalore / India

Mode of Engagement : Full-time

No. of Positions :

Educational Qualification :

B.E / B.Tech / M.Tech / MCA / Computer Science / IT

Industry :

IT / Data / AI / LegalTech / Enterprise Solutions

Notice Period :

Immediate Joiners Preferred

What We Are Looking For :

7–12 years of

hands-on experience

in designing, developing, and deploying

end-to-end data pipelines and ETL workflows

— not just using prebuilt tools, but

building from scratch

using Python and SQL.

Strong command of

Python programming

for data transformation, orchestration, and automation (e.g., using Pandas, Airflow, or custom schedulers).

Solid experience in

writing complex SQL queries , optimizing database performance, and designing schemas for large-scale systems.

Proven experience integrating

RESTful APIs

for data ingestion, transformation, and delivery pipelines.

Working knowledge of

AWS / GCP / Azure

for data storage, processing, and deployment (S3, EC2, Lambda, BigQuery, etc.).

Practical exposure to

Docker, Kubernetes , and

CI / CD pipelines

for automating and deploying ETL and data workloads.

Familiarity with

AI-driven data pipelines or automation workflows

is an added advantage.

Responsibilities :

Design, architect, and build ETL pipelines

from the ground up to extract, clean, transform, and load data across multiple systems.

Develop and deploy

custom Python-based data frameworks

to automate workflows and improve data quality.

Build and maintain

high-performance SQL queries

and database structures to support analytics and AI teams.

Develop and integrate

API-based data ingestion systems

(internal and external).

Deploy and manage workloads using

Docker, Kubernetes, and CI / CD

tools ensuring high availability and version control.

Work closely with product, AI, and analytics teams to

deliver intelligent, automated data solutions .

Implement

data validation, monitoring, and alerting

mechanisms for production pipelines.

Continuously optimize pipeline performance, cost efficiency, and scalability in cloud environments.

Qualifications :

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Proficiency in

Python (FastAPI, Flask, or Django) ,

SQL , and

REST API design .

Strong understanding of

ETL principles, data modeling, and pipeline orchestration

(Airflow / Prefect / Dagster).

Experience working with

AWS (S3, Lambda, EC2, Glue, Athena)

or equivalent GCP / Azure components.

Hands-on exposure to

Docker, Kubernetes , and

Git-based CI / CD

workflows.

Excellent problem-solving, debugging, and analytical skills with an

ownership mindset .