Python Data & Automation Engineer (AWS_SQL_ETL / ELT Focused)

Experience : 3 - 8 Years

Location : Noida / Gurugram / Bangalore / Pune

Notice Period : Immediate Joiner / Serving Notice Period

Employment Type : Full-time

Role Overview :

We are looking for an experienced Python Data & Automation Engineer with a primary focus on data engineering, ETL/ELT pipelines, SQL, and process automation - not backend web development. In this role, you will be responsible for creating robust database connections, extracting data via internal and external APIs, running high-performance data transformations using Pandas and NumPy, and automating pipelines across on-premises and AWS cloud environments.

Key Responsibilities :

1. ETL/ELT & Data Pipelines :

- Design, build, and optimize scalable ETL/ELT pipelines; automate the ingestion, cleansing, and validation of large structured and unstructured datasets.

2. Data Processing & Analytics :

- Build high-performance data manipulation, aggregation, and numerical computation routines using Pandas and NumPy.

3. Database Connectivity & SQL :

- Establish connections with relational and analytical databases using PyODBC and native connectors; write, tune, and optimize complex SQL queries, views, and stored procedures.

4. API Integration & Automation :

- Design and deploy automated extraction pipelines interacting with REST/SOAP APIs to eliminate manual reporting and batch processing.

5. Cloud & Modern Data Platforms :

- Integrate automated data workflows into AWS (specifically S3 and EC2) and cloud data warehouses like Snowflake.

6. Legacy System Migration :

- Support, integrate, and modernize legacy workflows, including migration touchpoints from SAS to modern Python pipelines.

7. Version Control & CI/CD :

- Utilize GitHub / Git for version control, code reviews, and pipeline automation.

Technical Skills & Qualifications :

Must-Have Skills :

- Experience : 3 to 8 years of direct hands-on experience in data engineering, ETL/ELT pipeline development, and data automation (not pure backend web/Django frameworks).

- Python for Data : Deep expertise in Python scripting with a primary focus on Pandas, NumPy, and automation utilities.

- Database & Connectivity : Strong SQL proficiency along with hands-on experience using PyODBC or similar database drivers.

- API Data Ingestion : Proven ability to extract and ingest data from RESTful APIs and web services.

- Cloud & Tooling : Hands-on experience with AWS (especially S3, EC2) and version control using GitHub.

Preferred / Good-to-Have Skills :

- Snowflake : Hands-on experience with Snowflake querying, architecture, or data loading.

- SAS Integration : Prior experience working with or migrating legacy SAS scripts into Python.

- Workflow Scheduling : Familiarity with orchestration and scheduling tools like Apache Airflow or Cron.