Data Engineer

We are looking for a skilled and motivated Data Engineer to design, build, and maintain scalable data infrastructure and pipelines. You will work closely with data scientists, analysts, and engineers to provide clean, reliable data for analytics, reporting, and machine learning.

Key Responsibilities:

Develop, construct, test, and maintain data architectures (e.g., databases, large-scale processing systems).

Build and optimize ETL/ELT pipelines to ingest data from diverse sources.

Collaborate with data scientists and analysts to understand data requirements and deliver solutions.

Ensure data quality, integrity, and security throughout the data lifecycle.

Manage and monitor data workflows and troubleshoot any pipeline failures.

Implement data modeling and warehousing solutions.

Automate manual processes and improve data delivery efficiency.

Stay updated with emerging data engineering trends and technologies.

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Proficiency in programming languages such as Python, Java, or Scala.

Strong experience with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).

Hands-on experience with ETL tools and workflow schedulers (e.g., Apache Airflow, Luigi).

Familiarity with big data technologies like Hadoop, Spark, Kafka, or similar.

Experience with cloud platforms (AWS, GCP, Azure) and their data services (e.g., S3, BigQuery, Redshift).

Understanding of data modeling, warehousing, and distributed systems.

Familiarity with version control and CI/CD pipelines.

Preferred Qualifications:

Experience with containerization and orchestration (Docker, Kubernetes).

Knowledge of real-time data streaming and processing.

Familiarity with data governance and compliance practices.

Certifications in cloud data engineering (AWS, GCP, Azure) are a plus.