We are seeking a skilled and motivated Data Engineer to design, build, and maintain scalable data infrastructure and pipelines that support analytics, machine learning, and business intelligence initiatives. As a key member of our data team, you will collaborate with data analysts, scientists, and software engineers to ensure the availability, reliability, and quality of our data systems.

Key Responsibilities:
Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and store structured and unstructured data.

Build and optimize data architectures and data models for analytics and reporting use cases.

Collaborate with data analysts and business stakeholders to define data requirements and deliver solutions.

Monitor and improve data pipeline performance, reliability, and scalability.

Implement and enforce data quality, security, and governance standards.

Work with cloud-based data infrastructure (e.g., AWS, GCP, Azure) and modern data stack tools.

Automate workflows and data integration processes.

Required Qualifications:
Bachelors degree in Computer Science, Data Engineering, Information Systems, or a related field.

2 5 years of experience in a data engineering or similar role.

Proficiency in SQL and experience with data pipeline tools (e.g., Apache Airflow, dbt, Luigi).

Experience with data warehousing solutions such as Snowflake, BigQuery, Redshift, or Azure Synapse.

Strong programming skills in Python, Java, or Scala.

Familiarity with cloud platforms (AWS, GCP, or Azure) and cloud-native data tools.

Knowledge of distributed systems and processing frameworks (e.g., Spark, Kafka).

Preferred Qualifications:
Experience with infrastructure-as-code and CI/CD for data (e.g., Terraform, GitHub Actions).

Understanding of data lake and lakehouse architectures.

Experience with real-time data processing and streaming analytics.

Exposure to data privacy, compliance, and security best practices.