Python Data & Automation Engineer_AWS_ETL_SQL

Crescendo Global Leadership Hiring India; Pune District, Gurugram District, Bengaluru; Híbrido; INR 1.200.000 - 2.400.000; Jornada completa

Descripción de la vacante

Crescendo Global Leadership Hiring India is seeking an experienced Python Data & Automation Engineer with a strong focus on ETL/ELT pipelines, SQL, and cloud automation. You will design robust data flows, build high-performance transformations using Pandas and NumPy, integrate APIs, and automate workflows across on-premises and AWS environments.

The role requires 3–8 years of hands-on data engineering experience, and you will collaborate with cross-functional teams to deliver scalable data

Formación

• 3–8 years of hands-on data engineering and ETL/ELT experience.
• Strong Python scripting with Pandas and NumPy.
• Solid SQL skills and database connectivity.
• Experience ingesting data from REST/SOAP APIs.
• Experience with AWS services (S3/EC2) and version control.

Responsabilidades

• Design, build, and optimize ETL/ELT pipelines to handle large datasets.
• Develop high-performance data processing with Pandas/NumPy.
• Establish relational and analytical DB connections using PyODBC.
• Create automated data ingestion via REST APIs and web services.
• Integrate data workflows with AWS S3/EC2 and Snowflake.
• Migrate legacy SAS scripts to Python pipelines.
• Utilize GitHub for version control and CI/CD.

Conocimientos

Data engineering

ETL pipelines

Python for data

SQL proficiency

API ingestion

AWS cloud

GitHub

Data automation

Pandas/NumPy

Herramientas

PyODBC

Snowflake

Apache Airflow

Cron

Descripción del empleo

Job Description: 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

• ETL/ELT & Data Pipelines: Design, build, and optimize scalable ETL/ELT pipelines; automate the ingestion, cleansing, and validation of large structured and unstructured datasets.
• Data Processing & Analytics: Build high-performance data manipulation, aggregation, and numerical computation routines using Pandas and NumPy.
• 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.
• API Integration & Automation: Design and deploy automated extraction pipelines interacting with REST/SOAP APIs to eliminate manual reporting and batch processing.
• Cloud & Modern Data Platforms: Integrate automated data workflows into AWS (specifically S3 and EC2) and cloud data warehouses like Snowflake.
• Legacy System Migration: Support, integrate, and modernize legacy workflows, including migration touchpoints from SAS to modern Python pipelines.
• 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.