Data Engineer with Python

Job Description:

We are seeking an experienced

Data Engineer

with over

10 years of expertise

in building scalable data solutions. The ideal candidate will have strong proficiency in

Python ,

SQL ,

ETL processes ,

data warehousing , and experience working with

cloud and big data technologies . This role requires excellent problem-solving skills, technical expertise, and the ability to collaborate across teams to deliver high-quality data solutions.

Key Responsibilities:

Design, develop, and maintain scalable

data pipelines, ETL workflows, and data integration solutions . Implement

data warehousing and data modeling

best practices across multiple platforms. Work with

cloud environments

(AWS, Azure, or GCP) to deploy and manage data solutions. Optimize

SQL queries and database performance

for large datasets. Leverage

big data technologies

such as Hadoop, Spark, and Kafka for high-volume data processing. Collaborate with cross-functional teams to ensure data quality, reliability, and governance. Apply

DevOps practices

(CICD, Docker, Kubernetes) for data deployment and automation. Contribute to data science initiatives by supporting

machine learning and statistical analysis

requirements. Required Skills & Experience:

10+ years of experience

in data engineering or a related role. Strong proficiency in

Python (Pandas, NumPy)

and

SQL . Hands-on experience with

ETL tools

(Apache Airflow, NiFi, Informatica, DataStage). Solid understanding of

data warehousing, data modeling, and database technologies

(SQL Server, PostgreSQL, MySQL, Snowflake, BigQuery, Redshift). Experience with

cloud platforms

(AWS, Azure, or GCP). Familiarity with

big data tools

(Hadoop, Spark, Kafka) - preferred. Exposure to

DevOps practices

including CI/CD, Docker, Kuber