We are seeking a skilled and detail-oriented Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support analytics, reporting, and data science initiatives.
You will work closely with data analysts, data scientists, and software engineers to ensure data quality, optimize performance, and drive data-driven decision-making.
Design, develop, and maintain reliable data pipelines using tools like Apache Spark, Kafka, Airflow, or DBT.
Build and optimize data models and architectures for data lakes and data warehouses (e.g., Snowflake, Redshift, BigQuery).
Develop ETL/ELT processes to ingest and transform data from multiple sources (e.g., APIs, databases, flat files).
Ensure data quality, integrity, security, and compliance with best practices and regulations (e.g., GDPR).
Collaborate with stakeholders to understand data requirements and deliver scalable solutions.
Monitor pipeline performance and troubleshoot data issues.
Maintain documentation for data systems, pipelines, and workflows.
Stay current with industry trends and emerging technologies in data engineering and analytics.
Bachelor's or Master’s degree in Computer Science, Engineering, Information Systems, or related field.
2+ years of experience in data engineering, data architecture, or related roles.
Strong experience with SQL and data modeling.
Proficiency in Python, Scala, or Java.
Hands-on experience with cloud platforms (AWS, GCP, Azure) and services like S3, Lambda, Redshift, or BigQuery.
Familiarity with data pipeline tools such as Apache Airflow, Kafka, or DBT.
Experience with CI/CD, Git, and containerization (Docker, Kubernetes) is a plus.
Excellent problem-solving and communication skills.
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