Data Engineer

Experience Level:

4 to 6 years of relevant IT experience

Job Overview:

We are looking for a skilled and motivated Data Engineer with strong experience in Python

programming and Google Cloud Platform (GCP) to join our data engineering team. The ideal

candidate will be responsible for designing, developing, and maintaining robust and scalable

ETL (Extract, Transform, Load) data pipelines. The role involves working with various GCP

services, implementing data ingestion and transformation logic, and ensuring data quality and

consistency across systems.

Key Responsibilities:

Design, develop, test, and maintain scalable ETL data pipelines using Python.

Work extensively on Google Cloud Platform (GCP) services such as:

Dataflow for real-time and batch data processing

Cloud Functions for lightweight serverless compute

BigQuery for data warehousing and analytics

Cloud Composer for orchestration of data workflows (based on Apache Airflow)

Google Cloud Storage (GCS) for managing data at scale

IAM for access control and security

Cloud Run for containerized applications

Perform data ingestion from various sources and apply transformation and cleansing

logic to ensure high-quality data delivery.

Implement and enforce data quality checks, validation rules, and monitoring.

Collaborate with data scientists, analysts, and other engineering teams to understand

data needs and deliver efficient data solutions.

Manage version control using GitHub and participate in CI/CD pipeline deployments for

data projects.

Write complex SQL queries for data extraction and validation from relational databases

such as SQL Server, Oracle, or PostgreSQL.

Document pipeline designs, data flow diagrams, and operational support procedures.

Required Skills:

4–6 years of hands-on experience in Python for backend or data engineering projects.

Strong understanding and working experience with GCP cloud services (especially

Dataflow, BigQuery, Cloud Functions, Cloud Composer, etc.).

Solid understanding of data pipeline architecture, data integration, and

transformation techniques.

Experience in working with version control systems like GitHub and knowledge of CI/CD

practices.

Strong experience in SQL with at least one enterprise database (SQL Server, Oracle,

PostgreSQL, etc.).

Good to Have (Optional Skills):

Experience working with Snowflake cloud data platform.

Hands-on knowledge of Databricks for big data processing and analytics.

Familiarity with Azure Data Factory (ADF) and other Azure data engineering tools.

Additional Details:

Excellent problem-solving and analytical skills.

Strong communication skills and ability to collaborate in a team environment.